Efficacy in Financial Rulemaking
Data
The root for this script is finreg. Most of the data are in finreg/data (some in a subfolder merged_resources). Others are up one level in FINREGRULEMAKE2/Data. This can and should be streamlined significantly.
Sophistication
File: Data/Dictionary_Terms.RData contains six objects (3 sets of measures for both comments and attachments)
1. Dictionary counts of technical terms used in comments and attachments
We use the Oxford Dictionary of Finance and Banking and the Merriam Webster law dictionary. While Black’s is a more common law dictionary, a complete version is not available online.
Objects: technical_terms_comments and technical_terms_attachment
Variables:
doc_id- the comment_url or attachment_url in the comments and attachments files in master.sqliteuk_law- UK law terms - this is in the file as I was curious how many of the terms would be in a UK law dictionary.banking- US banking terms in Merriam Webster’s banking dictionaryus_law- US law terms in Merriam Webster’s US law dictionary. We didn’t use Black’s law dictionary because it’s incomplete, as shown at the beginning of thedictionary_and_bluebook.Rfileoverlap- terms in both banking and us_lawdictionary_terms - banking + us_law - overlapComment- 1 if from the comments file in Master, 0 if from attachments
2. Tables and Figures
Counts of Tables and Figures. Looks at the maximum number of tables, with large jumps excluded. For example, a document with tables 1, 2, 3, and 99 would treat 99 as an error and say there were three tables. This mostly comes from bad OCRing or documents that have footnotes in between the word “table” and the table number.
Objects: Tables_and_Figures_attachments and Tables_and_Figures_comments
Variables:
comment_url- the comment_url or attachment_url in the comments and attachments files in master.sqliteFigures- counts of figuresTables- counts of tablesComment- 1 if from comments, 0 if from attachmentsVisualizations- sum of figures + tables
3. Bluebook legal citations
Counts of citations to US code, Supreme Court cases, appellate and district court cases, the code of federal regulations, and the federal register
Objects: bluebok_comments and bluebook_attachments
Variables:
Comment- 1 if from comments, 0 if from attachmentscomment_url- the comment_url or attachment_url in the comments and attachments files in master.sqliteUS_Code- counts of US code citationsSupreme_Court_Cases- counts of Supreme Court casesAppeals_and_District_Court_Cases- counts of citations to Appeals and district court casesCode_of_Federal_Regulations- counts of citations to CFRFederal_Register_Total- counts of citations to federal registerTotal_Legal_Citations- sum of above except comment dummy
# sophistication
load(here("data", "Dictionary_Terms.Rdata") %>% str_remove("finreg") )
# drop duplicates
technical_terms_comments %<>%
distinct()
technical_terms_attachments %<>%
distinct()
bluebook_comments %<>%
distinct()
bluebook_attachments %<>%
distinct() # summarize and merge term counts from comment text boxes and attachments
# max <- . %>% base::max(na.rm = TRUE)
# sum by comment url
#FIXME, why are these not unique!
bluebook_c <- bluebook_comments %>%
drop_na(Total_Legal_Citations) %>%
group_by(comment_url) %>%
dplyr::select(-comment) %>%
summarise_all(base::max)
# whereas these should not be uniqe to comment url
bluebook_a <- bluebook_attachments %>%
drop_na(Total_Legal_Citations) %>%
group_by(comment_url) %>%
dplyr::select(-comment) %>%
summarise_all(base::max)
# join both and max again
bluebook <- full_join(bluebook_a,
bluebook_c) %>%
group_by(comment_url) %>%
summarise_all(base::max)
# # check for unique comment_url
# bluebook %>% count(comment_url, sort = T)
# sum by comment url
#FIXME, why are these not unique!?
technical_terms_c <- technical_terms_comments %>%
drop_na(dictionary_terms) %>%
group_by(comment_url) %>%
dplyr::select(-comment) %>%
summarise_all(base::max)
# whereas these should not be uniqe to comment url
technical_terms_a <- technical_terms_attachments %>%
drop_na(dictionary_terms) %>%
group_by(comment_url) %>%
dplyr::select(-comment) %>%
summarise_all(base::max)
# join both and sum again
technical_terms <- full_join(technical_terms_a,
technical_terms_c) %>%
group_by(comment_url) %>%
summarise_all(base::max)
# # check for unique comment_url
# technical_terms %>% count(comment_url, sort = T)
full_join(technical_terms, bluebook) %>% kablebox()# check that they are the same
# full_join(bluebook, technical_terms)Assets
load(here::here("data", "commenter_assets.Rdata"))
d <- commenter_assets
#FIXME MOVE TO TOP
d$comment_url %<>% str_replace("document\\?D=", "comment/")
d %>% arrange(assets) %>%
dplyr::select(org_name, assets, revenue, comment_url) %>% kablebox()d %>% arrange(marketcap2) %>%
dplyr::select(org_name, marketcap, comment_url) %>% kablebox()d %>% arrange(-MeanContribAmount) %>%
dplyr::select(org_name, MeanContribAmount, comment_url) %>% kablebox()Efficacy
File: Data/attachment_efficacy_w_docket.csv.
Variables:
efficacy=cumulative_sequence_length_over_10
Other efficacy measures that we are not using:
- number_of_other_sequences_over_10
- number_of_other_sequences_over_25
- number_of_other_sequences_over_50
- number_of_other_sequences_over_100
- cumulative_sequence_length_over_10
- cumulative_sequence_length_over_25
- cumulative_sequence_length_over_50
- cumulative_sequence_length_over_100
- longest_sequence_length
- longest_repeated_text
# efficacy
efficacy_raw <- read_csv( here::here("data", "new_attachment_efficacy_w_docket.csv") %>% str_remove("finreg") )
# inspect
# efficacy_raw %>% distinct() %>% dplyr::select(attachment_url, fr_document_id_final) %>% add_count(attachment_url) %>% arrange(-n) %>% kablebox()
# # look for non-numeric values other than headers
# efficacy_raw %>%
# filter(!is.na(cumulative_sequence_length_over_10),
# comment_url != "comment_url") %>%
# mutate(efficacy = cumulative_sequence_length_over_10 %>% as.numeric() ) %>%
# filter(is.na(efficacy)) %>%
# dplyr::select(comment_url, cumulative_sequence_length_over_10)
# select needed vars. url is comment url (even for attachments)
efficacy <- efficacy_raw %>%
# make comment url
mutate(comment_url2 = attachment_url %>%
str_replace("https://downloads.regulations.gov/",
"https://www.regulations.gov/comment/" ) %>%
str_remove("/attachment_.*"),
comment_url = coalesce(comment_url, comment_url2),
efficacy = cumulative_sequence_length_over_10 %>% as.numeric()
) %>%
dplyr::select(comment_url,
efficacy) %>%
distinct()
# check for OCC comments (missing as of May 2022)
# efficacy %>% filter(str_detect(comment_url, "OCC"))
# check for CFPB comments (not missing, but failing to merge with d on URL?)
# efficacy %>% filter(str_detect(comment_url, "CFPB"))
efficacy %<>% drop_na(efficacy)
# take max
efficacy %<>%
group_by(comment_url) %>%
summarise_all(base::max)
efficacy %>% arrange(-efficacy) %>% kablebox()# d$comment_url %in% efficacy$comment_url %>% sum
# efficacy$comment_url %in% d$comment_url %>% sum
#efficacy %>% filter(str_detect(comment_url, "CFPB")) %>% kablebox()
d %<>% left_join(efficacy)
d %>% group_by(Agency) %>% count(is.na(efficacy))## # A tibble: 9 × 3
## # Groups: Agency [5]
## Agency `is.na(efficacy)` n
## <chr> <lgl> <int>
## 1 CFPB FALSE 2893
## 2 CFPB TRUE 8920
## 3 CFTC TRUE 3087
## 4 FRS FALSE 902
## 5 FRS TRUE 2481
## 6 NCUA FALSE 9
## 7 NCUA TRUE 69
## 8 SEC FALSE 1213
## 9 SEC TRUE 1778# check number of NAs
bluebook_comments %>%
summarise_all(is.na) %>%
summarise_all(sum)
# multiple per url?
bluebook_comments %>% count(comment_url, sort = T)
bluebook_attachments %>% count(comment_url, sort = T)
# example
bluebook_attachments %>% filter(comment_url == "https://www.regulations.gov/comment/OCC-2011-0008-0126") %>% kablebox()
bluebook_comments %>% filter(comment_url == "https://www.regulations.gov/comment/OCC-2011-0008-0126") %>% kablebox()
technical_terms_comments %>% count(comment_url, sort = T)
technical_terms_attachments %>% count(comment_url, sort = T)Join sophistication and asset data
# Join
d %<>%
left_join(bluebook %>% dplyr::select(comment_url, Total_Legal_Citations)) %>%
left_join(technical_terms %>% dplyr::select(comment_url, dictionary_terms))
d %>%
dplyr::select(comment_url, org_name, Total_Legal_Citations, dictionary_terms, assets, marketcap, MeanContribAmount) %>%
filter(!is.na(dictionary_terms)) %>%
kablebox()# write out missing comment urls
d %>%
filter(is.na(dictionary_terms)) %>% dplyr::select(comment_url) %>% write_csv(file = "dictionary_terms_missing.csv")
# FIXME Missing as of May 2022
# bluebook %>% filter(str_detect(comment_url, "CFPB-2019-0021-0406"))
# technical_terms %>% filter(str_detect(comment_url, "CFPB-2019-0021-0406"))
#FIXME DROP BAD EFFICACY COMMENTS
efficacy%<>% filter(!comment_url %in% c(
"https://comments.cftc.gov/Handlers/PdfHandler.ashx?id=23750",
"https://www.regulations.gov/comment/CFPB-2012-0029-0054"
))
# look for outliers
efficacy %>% arrange(-efficacy) %>% kablebox(
)technical_terms %>%
dplyr::select(comment_url, dictionary_terms) %>%
arrange(-dictionary_terms) %>% kablebox()#FIXME DROP BAD TECHICAL TERM MEASURE
technical_terms %<>% filter(!comment_url %in% c(
"https://www.regulations.gov/comment/OCC-2013-0008-0028"
))
#FIXME DROP BAD TECHICAL TERM MEASURE
technical_terms %<>% filter(!comment_url %in% c(
"https://www.regulations.gov/comment/OCC-2013-0008-0028"
))
bluebook %>%
dplyr::select(comment_url, Total_Legal_Citations) %>%
arrange(-Total_Legal_Citations) %>% kablebox()efficacyXsophistication <- bluebook %>%
dplyr::select(comment_url, Total_Legal_Citations) %>% drop_na(Total_Legal_Citations) %>%
left_join(
technical_terms %>%
dplyr::select(comment_url, dictionary_terms)
) %>%
left_join(efficacy) %>%
mutate(efficacy = replace_na(efficacy, 0),
org = ifelse(comment_url %in% d$comment_url, "Matched organization", "Individual or\nunmatched organization") )Matched vs. unmatched comments
# matched-by-terms
efficacyXsophistication %>%
ggplot() +
aes(x = dictionary_terms, fill = org) +
geom_histogram() +
facet_wrap("org", ncol = 1, scales = "free_y") +
scale_y_log10() +
labs(title = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "Number of Comments",
x = "Technical Terms in Comment",
fill = "")
efficacyXsophistication %>%
ggplot() +
aes(x = dictionary_terms, fill = org) +
geom_density(alpha = .5, color = NA) +
#facet_wrap("org", ncol = 1, scales = "free_y") +
scale_x_log10() +
labs(title = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "",
x = "Technical Terms in Comment",
fill = "") 
# matched-by-bluebook
efficacyXsophistication %>%
ggplot() +
aes(x = Total_Legal_Citations, fill = org) +
geom_histogram() +
facet_wrap("org", ncol = 1, scales = "free_y") +
scale_y_log10() +
labs(title = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "Number of Comments",
x = "Legal Citations in Comment",
fill = "")
efficacyXsophistication %>%
ggplot() +
aes(x = Total_Legal_Citations, fill = org) +
geom_density(alpha = .5, color = NA) +
#facet_wrap("org", ncol = 1, scales = "free_y") +
scale_x_log10() +
labs(title = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "",
x = "Legal Citations in Comment",
fill = "") 
# matched-by-efficacy
efficacyXsophistication %>%
ggplot() +
aes(x = efficacy, fill = org) +
geom_histogram() +
facet_wrap("org", ncol = 1, scales = "free_y") +
scale_y_log10() +
labs(title = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "Number of Comments",
x = "Lobbying Success\nn(Words From Comment\nAdded to Final Rule)",
fill = "")
efficacyXsophistication %>%
ggplot() +
aes(x = efficacy, fill = org) +
geom_density(alpha = .5, color = NA) +
#facet_wrap("org", ncol = 1, scales = "free_y") +
scale_x_log10() +
labs(title = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "Number of Comments",
x = "Lobbying Success\nn(Words From Comment\nAdded to Final Rule)",
fill = "") 
Efficacy by Sophistication
# efficacyXsophistication
efficacyXsophistication %>% arrange(-efficacy) %>% kablebox()eXsplot <- efficacyXsophistication %>% # filter(efficacy > 0) %>% #FIXME
ggplot() +
aes(x = dictionary_terms, y = efficacy) +
geom_point(aes(y = 10131, x = 7705), color = "red", shape = 0, size = 3) +
geom_point(alpha = .5) +
geom_smooth(method = "lm") +
labs(caption = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
y = "Lobbying Success\nn(Words From Comment\nAdded to Final Rule)",
x = "Technical Terms in Comment",
color = "") +
theme(legend.position = "bottom")
eXsplot +
annotate(y = 10131, x = 7705, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .8, hjust = -0.05, size = 3.5)
eXsplot +
scale_x_log10() +
scale_y_log10() +
annotate(y = 10131, x = 7705, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .8, hjust = 1.05, size = 3.5)
# color
eXsplot +
annotate(y = 10131, x = 7705, color = "red", geom = "text",
label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.",
vjust = .8, hjust = -0.05, size = 3.5) +
aes(color = org) + labs(color = "")
eXsplot +
scale_x_log10() +
scale_y_log10() +
aes(color = org)+ labs(color = "") +
annotate(y = 10131, x = 7705, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .8, hjust = 1.05, size = 3.5)
# legal citations
eXsplot <- efficacyXsophistication %>% # filter(efficacy > 0) %>% #FIXME
ggplot() +
aes(x = Total_Legal_Citations, y = efficacy) +
geom_point(alpha = .5) +
geom_smooth(method = "lm") +
labs(caption = str_c("Comments on Dodd-Frank Rules, N = ", nrow(efficacyXsophistication) %>% prettyNum(big.mark = ",")),
color = "",
y = "Lobbying Success\nn(Words From Comment\nAdded to Final Rule)",
x = "Legal Citations in Comment") +
geom_point(aes(x = 31, y = 10131), color = "red", shape = 0, size = 3)+
theme(legend.position = "bottom")
eXsplot +
annotate(x = 31, y = 10131, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .8, hjust = -0.05, size = 3.5)
eXsplot +
scale_x_log10() +
scale_y_log10() +
annotate(y = 10131, x = 31, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .5, hjust = 1.05, size = 3.5)
# color
eXsplot +
annotate(x = 31, y = 10131, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .8, hjust = -0.05, size = 3.5) + aes(color = org) + labs(color = "")
eXsplot +
scale_x_log10() +
scale_y_log10() +
aes(color = org) + labs(color = "") +
annotate(y = 10131, x = 31, color = "red", geom = "text", label = "Comment & Marked-up Draft Rule,\nU.S. Chamber of Commerce et al.", vjust = .8, hjust = 1.05, size = 3.5)
Number of comments per agency
Technical terms measured for 20,922 of 21,352 comments.
# matches
d %>%
count(Agency, name = "n comments matched with org") %>%
left_join(
d %>%
filter(comment_url %in% technical_terms$comment_url) %>%
count(Agency, name = "n with dictionary terms measured")
) %>%
left_join(
d %>%
dplyr::select(-efficacy) %>%
filter(comment_url %in% efficacy$comment_url) %>%
count(Agency, name = "n with efficacy measured")
) %>%
kablebox()| Agency | n comments matched with org | n with dictionary terms measured | n with efficacy measured |
|---|---|---|---|
| CFPB | 11813 | 11438 | 2892 |
| CFTC | 3087 | 3083 | NA |
| FRS | 3383 | 3383 | 902 |
| NCUA | 78 | 27 | 9 |
| SEC | 2991 | 2991 | 1213 |
Plots
Sophistication x assets
Legal citations x assets
# assets-blue
b <- d %>% filter(!is.na(dictionary_terms))
b %>% dplyr::select(org_name, Total_Legal_Citations, org_resources, comment_url) %>%
drop_na(org_name, org_resources) %>%
kablebox()# FDIC ASSTS
# FDIC ASSTS
p <- b %>%
filter(!is.na(`FDIC_Institutions-bestMatch:ASSET`)) %>%
ggplot() +
aes(x = `FDIC_Institutions-bestMatch:ASSET`, # %>% log(),
y = Total_Legal_Citations ) +
geom_point(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Assets",
y = "Legal Citations",
title = "FDIC-Insured Banks")
p
p +
scale_y_log10() +
scale_x_log10()
# nonprofits
p <- b %>%
ggplot() +
aes(x = assets,
y = Total_Legal_Citations) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
)+
labs(x = "Assets",
y = "Legal Citations",
title = "Nonprofits")
p
p +
scale_y_log10() +
scale_x_log10()
# contribution
p <- b %>%
ggplot() +
aes(x = MeanContribAmount/1000,
y = Total_Legal_Citations) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Mean PAC Contribution ($1,000)",
y = "Legal Citations",
title = "Campaign Donors")
p
p +
scale_y_log10() +
scale_x_log10()
p <- b %>%
#filter(marketcap2 > 1000000) %>%
ggplot() +
aes(x = marketcap2/1000000000,
y = Total_Legal_Citations) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Market Capitalization (Billions)",
y = "Legal Citations",
title = "Publicly-Traded Companies")
p
p +
scale_y_log10() +
scale_x_log10() +
xlim(c(0, 400))
# b %>% count(comment_agency, is.na( assets))
b %>% filter(Total_Legal_Citations>10,
!is.na(org_name)) %>% dplyr::select(org_name,Total_Legal_Citations, comment_url, everything()) %>% arrange(-Total_Legal_Citations) %>% kablebox()| org_name | Total_Legal_Citations | comment_url | docket_id | comment_docket_count | comment_agency | comment_org_name | comment_submitter_name | CIK_name | CreditUnions_name | FDIC_Institutions_name | FFIECInstitutions_name | SEC_Institutions_name | compustat_resources_name | nonprofits_resources_name | opensecrets_resources_jwVersion_name | best_match_name | best_match_score | best_match_type | FDIC_Institutions-bestMatch:ASSET | FDIC_Institutions-bestMatch:STNAME | CIK-bestMatch:marketcap | SEC_Institutions-bestMatch:Ticker | compustat_resources-bestMatch:marketcap | compustat_resources-bestMatch:naics | nonprofits_resources-bestMatch:assets | nonprofits_resources-bestMatch:revenue | nonprofits_resources-bestMatch:ein | opensecrets_resources_jwVersion-bestMatch:MeanContribAmountPerYearContributed | opensecrets_resources_jwVersion-bestMatch:TotalContribAmount | matches | org_type | org_resources | opensecrets_resources_name | org_comments | best_match_org_comments | marketcap | marketcap2 | Agency | Org_type | payday | MeanContribAmount | TotalContribAmount | assets | revenue | naics | Total Assets | efficacy | dictionary_terms |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| advance financial | 273 | https://www.regulations.gov/comment/CFPB-2016-0025-3913 | CFPB-2016-0025 | 1 | CFPB | advance financial | mike hodges | NA | advance financial | NA | NA | NA | NA | NA | NA | advance financial | 1.0000000 | Credit Union | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | advance financial-Credit Union | Credit Union | NA | NA | 1967 | 1967 | NA | NA | CFPB | Credit Union | Payday Loan Rules | NA | NA | 147073247 | NA | NA | 147073247 | NA | 16394 |
| consumer mortgage coalition | 149 | https://www.regulations.gov/comment/CFPB-2014-0033-0164 | CFPB-2014-0033 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 590 | 16402 |
| consumer mortgage coalition | 144 | https://www.regulations.gov/comment/CFPB-2011-0007-0006 | CFPB-2011-0007 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 442 | 7083 |
| consumer mortgage coalition | 144 | https://www.regulations.gov/comment/CFPB-2011-0005-0008 | CFPB-2011-0005 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 156 | 7083 |
| consumer mortgage coalition | 144 | https://www.regulations.gov/comment/CFPB-2011-0006-0006 | CFPB-2011-0006 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 1013 | 7083 |
| consumer mortgage coalition | 144 | https://www.regulations.gov/comment/CFPB-2011-0003-0009 | CFPB-2011-0003 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 722 | 7083 |
| international money management | 130 | https://www.regulations.gov/comment/CFPB-2012-0029-0054 | CFPB-2012-0029 | 1 | CFPB | money management international | zynda sellers | international money management | NA | NA | NA | NA | NA | NA | NA | international money management | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | international money management-CIK | CIK | NA | NA | 4 | 4 | NA | NA | CFPB | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 46512 | 22908 |
| national consumer law center | 114 | https://www.regulations.gov/comment/CFPB-2013-0033-0386 | CFPB-2013-0033 | 1 | CFPB | national consumer law center | margot saunders | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | NA | 26080 |
| national consumer law center | 96 | https://www.regulations.gov/comment/CFPB-2016-0020-5831 | CFPB-2016-0020 | 1 | CFPB | national consumer law center | lauren saunders | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | 1899 | 14194 |
| clearing house association | 95 | https://www.sec.gov/comments/s7-41-11/s74111-210.pdf | S7-41-11 | 1 | SEC | clearing house association | securities industry financial markets association | NA | NA | NA | NA | NA | NA | clearing house association | NA | clearing house association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 135272860 | NA | NA | clearing house association-Nonprofit | Nonprofit | NA | NA | 36 | 38 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 2597 | 21526 |
| securities industry financial markets association | 95 | https://www.federalreserve.gov/SECRS/2012/March/20120305/R-1432/R-1432_021312_104703_532361297436_1.pdf | R-1432 | 1 | FRS | securities industry financial markets association | american bankers association | securities industry financial markets association | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association-CIK | CIK | NA | NA | 94 | 96 | NA | NA | FRS | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 2587 | 21507 |
| securities experts roundtable | 95 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=56630 | CFTC-2012-0019 | 1 | CFTC | securities industry financial markets association american bankers association financial services roundtable clearing house association | randolph snook | NA | NA | NA | NA | NA | NA | securities experts roundtable | NA | securities experts roundtable | 0.3367721 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 203248172 | NA | NA | securities experts roundtable-Nonprofit | Nonprofit | NA | NA | 3 | 3 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 21526 |
| national consumer law center | 86 | https://www.regulations.gov/comment/CFPB-2014-0033-0136 | CFPB-2014-0033 | 1 | CFPB | national consumer law center | alys cohen | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | 3202 | 10933 |
| mercatus center | 84 | https://www.sec.gov/comments/s7-03-13/s70313-335.pdf | S7-03-13 | 1 | SEC | mercatus center george mason university | hester peirce | NA | NA | NA | NA | NA | NA | mercatus center | NA | mercatus center | 0.6382409 | Nonprofit | NA | NA | NA | NA | NA | NA | 5568496 | 11734489 | 541436224 | NA | NA | mercatus center-Nonprofit | Nonprofit | 5568496 | NA | 6 | 5 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 5568496 | 11734489 | NA | NA | NA | 8772 |
| east bay community law center | 82 | https://www.regulations.gov/comment/CFPB-2013-0033-0393 | CFPB-2013-0033 | 1 | CFPB | east bay community law center | ted mermin | NA | NA | NA | NA | NA | NA | east bay community law center | NA | east bay community law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 4642138 | 2652633 | 943042565 | NA | NA | east bay community law center-Nonprofit | Nonprofit | 4642138 | NA | 1 | 1 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 4642138 | 2652633 | NA | NA | NA | 20190 |
| center responsible lending | 80 | https://www.regulations.gov/comment/CFPB-2016-0025-154512 | CFPB-2016-0025 | 1 | CFPB | center responsible lending | rebecca born | NA | NA | NA | NA | NA | NA | center responsible lending | NA | center responsible lending | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 4205309 | 7906750 | 743043913 | NA | NA | center responsible lending-Nonprofit | Nonprofit | 4205309 | NA | 40 | 48 | NA | NA | CFPB | Nonprofit (IRS Data) | Payday Loan Rules | NA | NA | 4205309 | 7906750 | NA | NA | 3794 | 47531 |
| adventist community services north america | 75 | https://www.regulations.gov/comment/CFPB-2016-0025-142779 | CFPB-2016-0025 | 1 | CFPB | community financial services association america | dennis shaul | NA | NA | NA | NA | NA | NA | adventist community services north america | NA | adventist community services north america | 0.9062883 | Nonprofit | NA | NA | NA | NA | NA | NA | 2522436 | 903100 | 203519054 | NA | NA | adventist community services north america-Nonprofit | Nonprofit | 2522436 | NA | 8 | 7 | NA | NA | CFPB | Nonprofit (IRS Data) | Payday Loan Rules | NA | NA | 2522436 | 903100 | NA | NA | 1761 | 11944 |
| international finance | 73 | https://www.sec.gov/comments/s7-02-13/s70213-56.pdf | S7-34-10;S7-40-11;S7-02-13 | 1 | SEC | international finance | annemarie leroy | international finance | NA | NA | NA | NA | NA | NA | NA | international finance | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | international finance-CIK | CIK | NA | NA | 3 | 3 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 265 | 6253 |
| united trustees association | 63 | https://www.regulations.gov/comment/CFPB-2014-0033-0056 | CFPB-2014-0033 | 1 | CFPB | executive office united states trustees | lisa tracy | NA | NA | NA | NA | NA | NA | united trustees association | NA | united trustees association | 0.6750248 | Nonprofit | NA | NA | NA | NA | NA | NA | 281328 | 564659 | 953953008 | NA | NA | united trustees association-Nonprofit | Nonprofit | 281328 | NA | 1 | 1 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 281328 | 564659 | NA | NA | 232 | 1201 |
| better markets | 62 | https://www.sec.gov/comments/s7-02-13/s70213-42.pdf | S7-34-10;S7-40-11;S7-02-13 | 1 | SEC | better markets | dennis m kelleher | NA | NA | NA | NA | NA | NA | better markets | NA | better markets | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3898749 | 3022839 | 272227363 | NA | NA | better markets-Nonprofit | Nonprofit | 3898749 | NA | 156 | 158 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3898749 | 3022839 | NA | NA | 598 | 5253 |
| clearing house association | 61 | https://www.sec.gov/comments/s7-41-11/s74111-207.pdf | S7-41-11 | 1 | SEC | clearing house association | securities industry financial markets association | NA | NA | NA | NA | NA | NA | clearing house association | NA | clearing house association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 135272860 | NA | NA | clearing house association-Nonprofit | Nonprofit | NA | NA | 36 | 38 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 4409 | 18712 |
| securities industry financial markets association | 61 | https://www.federalreserve.gov/SECRS/2012/March/20120305/R-1432/R-1432_021312_104404_346801484756_1.pdf | R-1432 | 1 | FRS | securities industry financial markets association | american bankers association | securities industry financial markets association | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association-CIK | CIK | NA | NA | 94 | 96 | NA | NA | FRS | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 4482 | 18709 |
| securities experts roundtable | 61 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=56631 | CFTC-2012-0019 | 1 | CFTC | securities industry financial markets association american bankers association financial services roundtable clearing house association | randolph snook | NA | NA | NA | NA | NA | NA | securities experts roundtable | NA | securities experts roundtable | 0.3367721 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 203248172 | NA | NA | securities experts roundtable-Nonprofit | Nonprofit | NA | NA | 3 | 3 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 18712 |
| american land title association | 57 | https://www.regulations.gov/comment/CFPB-2012-0028-2732 | CFPB-2012-0028 | 1 | CFPB | american land title association | steven gottheim | NA | NA | NA | NA | NA | NA | american land title association | NA | american land title association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 460662435 | NA | NA | american land title association-Nonprofit | Nonprofit | NA | NA | 10 | 11 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 10519520 | 6394017 | NA | NA | NA | 11724 |
| american land title association | 57 | https://www.regulations.gov/comment/CFPB-2012-0028-2782 | CFPB-2012-0028 | 1 | CFPB | american land title association | steven gottheim | NA | NA | NA | NA | NA | NA | american land title association | NA | american land title association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 460662435 | NA | NA | american land title association-Nonprofit | Nonprofit | NA | NA | 10 | 11 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 10519520 | 6394017 | NA | NA | NA | 11724 |
| institute international bankers | 56 | https://www.federalreserve.gov/SECRS/2013/May/20130517/R-1438/R-1438_043013_111113_555179652070_1.pdf | R-1438 | 1 | FRS | institute international bankers | sarah miller | NA | NA | NA | NA | NA | NA | institute international bankers | NA | institute international bankers | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3623362 | 4528193 | 237296309 | NA | NA | institute international bankers-Nonprofit | Nonprofit | 3623362 | NA | 38 | 38 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3623362 | 4528193 | NA | NA | 1283 | 24811 |
| international finance | 52 | https://www.sec.gov/comments/s7-08-12/s70812-39.pdf | S7-08-12 | 1 | SEC | international finance | annemarie leroy | international finance | NA | NA | NA | NA | NA | NA | NA | international finance | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | international finance-CIK | CIK | NA | NA | 3 | 3 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 5160 |
| us chamber commerce | 52 | https://www.federalreserve.gov/SECRS/2013/May/20130521/R-1438/R-1438_043013_111114_389717962083_1.pdf | R-1438 | 1 | FRS | us chamber commerce | center capital markets competitiveness | NA | NA | NA | NA | NA | NA | NA | us chamber commerce | us chamber commerce | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | 85367723.7 | 512206342 | us chamber commerce-OpenSecrets | OpenSecrets | NA | us chamber commerce | 68 | 68 | NA | NA | FRS | PAC Donor (CRP Data) | All Other Rules | 85367723.7 | 512206342 | NA | NA | NA | NA | 70 | 6913 |
| financial services roundtable | 52 | https://www.federalreserve.gov/SECRS/2011/March/20110303/R-1404/R-1404_022211_67462_559315186904_1.pdf | R-1404 | 1 | FRS | financial services roundtable | steve bartlett | NA | NA | NA | NA | NA | NA | financial services roundtable | NA | financial services roundtable | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 10769784 | 19955247 | 360753125 | NA | NA | financial services roundtable-Nonprofit | Nonprofit | 10769784 | NA | 94 | 96 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | 347142.9 | 34020000 | 10769784 | 19955247 | NA | NA | 1099 | 8175 |
| consumer mortgage coalition | 51 | https://www.regulations.gov/comment/CFPB-2014-0033-0144 | CFPB-2014-0033 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 401 | 5891 |
| securities industry financial markets association | 51 | https://www.sec.gov/comments/s7-23-07/s72307-8.pdf | S7-23-07 | 1 | SEC | securities industry financial markets association | ira d hammerman | securities industry financial markets association | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association-CIK | CIK | NA | NA | 94 | 96 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 3863 |
| clearing house association | 51 | https://www.federalreserve.gov/SECRS/2012/May/20120501/R-1438/R-1438_042712_107270_542775340448_1.pdf | R-1438 | 1 | FRS | clearing house association | llc | NA | NA | NA | NA | NA | NA | clearing house association | NA | clearing house association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 135272860 | NA | NA | clearing house association-Nonprofit | Nonprofit | NA | NA | 36 | 38 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 62 | 68442 |
| national consumer law center | 49 | https://www.regulations.gov/comment/CFPB-2013-0002-0876 | CFPB-2013-0002 | 1 | CFPB | national consumer law center | diane thompson | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | 152 | 3789 |
| california reinvestment coalition | 48 | https://www.regulations.gov/comment/CFPB-2014-0033-0117 | CFPB-2014-0033 | 1 | CFPB | california reinvestment coalition | maeve brown | NA | NA | NA | NA | NA | NA | california reinvestment coalition | NA | california reinvestment coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 1163000 | 696419 | 943153815 | NA | NA | california reinvestment coalition-Nonprofit | Nonprofit | 1163000 | NA | 12 | 13 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 1163000 | 696419 | NA | NA | 544 | 2677 |
| consumer data industry association | 45 | https://www.regulations.gov/comment/CFPB-2016-0020-4318 | CFPB-2016-0020 | 1 | CFPB | consumer data industry association | stuart pratt | NA | NA | NA | NA | NA | NA | consumer data industry association | NA | consumer data industry association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3858601 | 3899041 | 430164315 | NA | NA | consumer data industry association-Nonprofit | Nonprofit | 3858601 | NA | 9 | 16 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3858601 | 3899041 | NA | NA | 581 | 3154 |
| council federal home loan banks | 45 | https://www.federalreserve.gov/SECRS/2012/September/20120912/R-1438/R-1438_043012_107236_478911121698_1.pdf | R-1438 | 1 | FRS | federal home loan banks | federal home loan banks | NA | NA | NA | NA | NA | NA | council federal home loan banks | NA | council federal home loan banks | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 856845 | 2108082 | 541877922 | NA | NA | council federal home loan banks-Nonprofit | Nonprofit | 856845 | NA | 3 | 6 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | 856845 | 2108082 | NA | NA | 42 | 3630 |
| texas mortgage bankers association | 45 | https://www.federalreserve.gov/SECRS/2011/September/20110913/R-1417/R-1417_072211_83618_591648672754_1.pdf | R-1417_V1 | 1 | FRS | mortgage bankers association | david h stevens | NA | NA | NA | NA | NA | NA | texas mortgage bankers association | NA | texas mortgage bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 1493337 | 1255751 | 750684612 | NA | NA | texas mortgage bankers association-Nonprofit | Nonprofit | 1493337 | NA | 66 | 69 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | 1493337 | 1255751 | NA | NA | NA | 7801 |
| qbe insurance | 44 | https://www.regulations.gov/comment/CFPB-2012-0034-0060 | CFPB-2012-0034 | 1 | CFPB | qbe first insurance agency | james novak | qbe insurance | NA | NA | NA | NA | NA | NA | NA | qbe insurance | 0.9587369 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | qbe insurance-CIK | CIK | NA | NA | 2 | 2 | NA | NA | CFPB | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 619 | 2218 |
| qbe insurance | 44 | https://www.regulations.gov/comment/CFPB-2012-0033-0102 | CFPB-2012-0033 | 1 | CFPB | qbe first insurance agency | james novak | qbe insurance | NA | NA | NA | NA | NA | NA | NA | qbe insurance | 0.9587369 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | qbe insurance-CIK | CIK | NA | NA | 2 | 2 | NA | NA | CFPB | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 2218 |
| consumer mortgage coalition | 44 | https://www.regulations.gov/comment/CFPB-2012-0028-2765 | CFPB-2012-0028 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | NA | 9630 |
| clearing house | 44 | https://www.federalreserve.gov/SECRS/2016/August/20160811/R-1534/R-1534_060316_130304_375681878754_1.pdf | R-1534 | 1 | FRS | clearing house | aba | NA | NA | NA | NA | NA | NA | NA | clearing house | clearing house | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1449500.0 | 8697000 | clearing house-OpenSecrets | OpenSecrets | NA | clearing house | 15 | 16 | NA | NA | FRS | PAC Donor (CRP Data) | All Other Rules | 1449500.0 | 8697000 | NA | NA | NA | NA | NA | 10601 |
| dentons us | 43 | https://www.regulations.gov/comment/CFPB-2016-0025-148826 | CFPB-2016-0025 | 1 | CFPB | dentons us | goldberg dentons | NA | NA | NA | NA | NA | NA | NA | dentons us | dentons us | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | dentons us-OpenSecrets | OpenSecrets | NA | dentons us | 1 | 1 | NA | NA | CFPB | PAC Donor (CRP Data) | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 371 | 3499 |
| 1st mariner bank | 43 | https://www.regulations.gov/comment/CFPB-2016-0025-142849 | CFPB-2016-0025 | 1 | CFPB | onemain holdings inc mariner finance llc 1st franklin financial | stephen schaller | 1st mariner bank | NA | NA | NA | NA | NA | NA | NA | 1st mariner bank | 0.6205107 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1st mariner bank-CIK | CIK | NA | NA | 1 | 1 | NA | NA | CFPB | Filed with SEC (CIK Data) | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 654 | 3422 |
| consumer mortgage coalition | 43 | https://www.regulations.gov/comment/CFPB-2014-0019-0256 | CFPB-2014-0019 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 421 | 3751 |
| institute curricular initiatives ici | 43 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=57474 | CFTC-2012-0023 | 1 | CFTC | investment company institute ici | karrie mcmillan | NA | NA | NA | NA | NA | NA | institute curricular initiatives ici | NA | institute curricular initiatives ici | 0.7794267 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 471886741 | NA | NA | institute curricular initiatives ici-Nonprofit | Nonprofit | NA | NA | 22 | 22 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 13372 |
| consumer mortgage coalition | 41 | https://www.regulations.gov/comment/CFPB-2013-0018-0274 | CFPB-2013-0018 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 1498 | 14287 |
| national consumer law center | 40 | https://www.regulations.gov/comment/CFPB-2012-0034-0098 | CFPB-2012-0034 | 1 | CFPB | national consumer law center | margot saunders | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | 1084 | 6874 |
| national consumer law center | 40 | https://www.regulations.gov/comment/CFPB-2012-0028-2811 | CFPB-2012-0028 | 1 | CFPB | national consumer law center | diane thompson | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | NA | 5165 |
| nationwide mutual insurance | 40 | https://www.federalreserve.gov/SECRS/2012/June/20120604/R-1438/R-1438_042612_107213_511650085598_1.pdf | R-1438 | 1 | FRS | nationwide mutual insurance | mark r thresher | nationwide mutual insurance | NA | NA | NA | NA | NA | NA | NA | nationwide mutual insurance | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | nationwide mutual insurance-CIK | CIK | NA | NA | 8 | 8 | NA | NA | FRS | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 60 | 2292 |
| fidelity management research | 40 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=42179 | CFTC-2011-0020 | 1 | CFTC | fidelity management research | scott goebel | NA | NA | NA | NA | NA | NA | NA | fidelity management research | fidelity management research | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | 4910166.7 | 29461000 | fidelity management research-OpenSecrets | OpenSecrets | NA | fidelity management research | 14 | 14 | NA | NA | CFTC | PAC Donor (CRP Data) | All Other Rules | 4910166.7 | 29461000 | NA | NA | NA | NA | NA | 2215 |
| select portfolio servicing | 39 | https://www.regulations.gov/comment/CFPB-2012-0033-0150 | CFPB-2012-0033 | 1 | CFPB | select portfolio servicing | jason miller | select portfolio servicing | NA | NA | NA | NA | NA | NA | NA | select portfolio servicing | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | select portfolio servicing-CIK | CIK | NA | NA | 6 | 6 | NA | NA | CFPB | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 25 | 9791 |
| securities industry financial markets association | 39 | https://www.federalreserve.gov/SECRS/2011/June/20110621/R-1411/R-1411_060911_81224_521506409071_1.pdf | R-1411 | 1 | FRS | securities industry financial markets association | richard dorfman | securities industry financial markets association | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association-CIK | CIK | NA | NA | 94 | 96 | NA | NA | FRS | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 16102 |
| american guild organists | 38 | https://www.regulations.gov/comment/CFPB-2011-0031-0021 | CFPB-2011-0031 | 1 | CFPB | american guild appraisers | matthew schneider | NA | NA | NA | NA | NA | NA | american guild organists | NA | american guild organists | 0.9217695 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 66103635 | NA | NA | american guild organists-Nonprofit | Nonprofit | NA | NA | 1 | 1 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 2633 |
| structured finance industry | 37 | https://www.sec.gov/comments/s7-14-11/s71411-488.pdf | S7-14-11 | 1 | SEC | structured finance industry | NA | NA | NA | NA | NA | NA | NA | structured finance industry | NA | structured finance industry | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 462258052 | NA | NA | structured finance industry-Nonprofit | Nonprofit | NA | NA | 15 | 15 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 25942 |
| structured finance industry | 37 | https://www.federalreserve.gov/SECRS/2013/December/20131219/R-1411/R-1411_103013_111495_377905725574_1.pdf | R-1411 | 1 | FRS | structured finance industry | richard johns | NA | NA | NA | NA | NA | NA | structured finance industry | NA | structured finance industry | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 462258052 | NA | NA | structured finance industry-Nonprofit | Nonprofit | NA | NA | 15 | 15 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 26018 |
| american muslim consumer consortium | 36 | https://www.regulations.gov/comment/CFPB-2013-0033-0241 | CFPB-2013-0033 | 1 | CFPB | consumer relations consortium | stephanie eidelman | NA | NA | NA | NA | NA | NA | american muslim consumer consortium | NA | american muslim consumer consortium | 0.6832512 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 461204761 | NA | NA | american muslim consumer consortium-Nonprofit | Nonprofit | NA | NA | 3 | 3 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 12732 |
| national consumer law center | 36 | https://www.regulations.gov/comment/CFPB-2011-0008-1294 | CFPB-2011-0008 | 1 | CFPB | national consumer law center | alys cohen | NA | NA | NA | NA | NA | NA | national consumer law center | NA | national consumer law center | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 17440205 | 6936521 | 42488502 | NA | NA | national consumer law center-Nonprofit | Nonprofit | 17440205 | NA | 55 | 55 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 17440205 | 6936521 | NA | NA | 468 | 6013 |
| texas mortgage bankers association | 36 | https://www.regulations.gov/comment/CFPB-2012-0022-0141 | CFPB-2012-0022 | 1 | CFPB | mortgage bankers association | ken markison | NA | NA | NA | NA | NA | NA | texas mortgage bankers association | NA | texas mortgage bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 1493337 | 1255751 | 750684612 | NA | NA | texas mortgage bankers association-Nonprofit | Nonprofit | 1493337 | NA | 66 | 69 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 1493337 | 1255751 | NA | NA | 226 | 6495 |
| better markets | 36 | https://www.sec.gov/comments/s7-06-13/s70613-410.pdf | S7-06-13 | 1 | SEC | better markets | dennis m kelleher | NA | NA | NA | NA | NA | NA | better markets | NA | better markets | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3898749 | 3022839 | 272227363 | NA | NA | better markets-Nonprofit | Nonprofit | 3898749 | NA | 156 | 158 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3898749 | 3022839 | NA | NA | NA | 2399 |
| center responsible lending | 36 | https://www.federalreserve.gov/SECRS/2011/November/20111129/R-1417/R-1417_072211_84149_582986006434_1.pdf | R-1417_V1 | 1 | FRS | center responsible lending | national consumer law center | NA | NA | NA | NA | NA | NA | center responsible lending | NA | center responsible lending | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 4205309 | 7906750 | 743043913 | NA | NA | center responsible lending-Nonprofit | Nonprofit | 4205309 | NA | 40 | 48 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | 4205309 | 7906750 | NA | NA | NA | 6007 |
| natural gas supply association | 36 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=59673 | CFTC-2013-0107 | 1 | CFTC | natural gas supply association | ryan barry | NA | NA | NA | NA | NA | NA | natural gas supply association | NA | natural gas supply association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3630494 | 2852594 | 520823671 | NA | NA | natural gas supply association-Nonprofit | Nonprofit | 3630494 | NA | 14 | 17 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3630494 | 2852594 | NA | NA | NA | 6440 |
| world bank | 36 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=58958 | CFTC-2011-0049 | 1 | CFTC | world bank | annemarie leroy | NA | NA | NA | NA | NA | NA | NA | world bank | world bank | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | world bank-OpenSecrets | OpenSecrets | NA | world bank | 5 | 5 | NA | NA | CFTC | PAC Donor (CRP Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4746 |
| natural gas supply association | 36 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=59674 | CFTC-2013-0098 | 1 | CFTC | natural gas supply association | ryan barry | NA | NA | NA | NA | NA | NA | natural gas supply association | NA | natural gas supply association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3630494 | 2852594 | 520823671 | NA | NA | natural gas supply association-Nonprofit | Nonprofit | 3630494 | NA | 14 | 17 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3630494 | 2852594 | NA | NA | NA | 6440 |
| clearing house association | 35 | https://www.federalreserve.gov/SECRS/2016/August/20160812/R-1536/R-1536_072216_130358_404900544091_1.pdf | R-1536 | 1 | FRS | clearing house association | llc | NA | NA | NA | NA | NA | NA | clearing house association | NA | clearing house association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 135272860 | NA | NA | clearing house association-Nonprofit | Nonprofit | NA | NA | 36 | 38 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 9976 |
| consumer mortgage coalition | 34 | https://www.regulations.gov/comment/CFPB-2013-0033-0322 | CFPB-2013-0033 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | NA | 1815 |
| clearing house association | 34 | https://www.federalreserve.gov/SECRS/2016/April/20160401/R-1529/R-1529_032116_130242_645806703457_1.pdf | R-1529 | 1 | FRS | clearing house association | gregory baer | NA | NA | NA | NA | NA | NA | clearing house association | NA | clearing house association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | NA | NA | 135272860 | NA | NA | clearing house association-Nonprofit | Nonprofit | NA | NA | 36 | 38 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 2561 |
| natl assn retail collection attorneys | 33 | https://www.regulations.gov/comment/CFPB-2013-0005-0055 | CFPB-2013-0005 | 1 | CFPB | national association retail collection attorneys | louis freedman | NA | NA | NA | NA | NA | NA | NA | natl assn retail collection attorneys | natl assn retail collection attorneys | 0.9933293 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | 318333.3 | 955000 | natl assn retail collection attorneys-OpenSecrets | OpenSecrets | NA | natl assn retail collection attorneys | 5 | 5 | NA | NA | CFPB | PAC Donor (CRP Data) | All Other Rules | 318333.3 | 955000 | NA | NA | NA | NA | 148 | 1243 |
| american bar association | 33 | https://www.sec.gov/comments/s7-12-15/s71215-67.pdf | S7-12-15 | 1 | SEC | american bar association | david m lynn | american bar association | NA | NA | NA | NA | NA | NA | NA | american bar association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | american bar association-CIK | CIK | NA | NA | 42 | 42 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | 239942508 | 140654146 | NA | NA | NA | 10907 |
| securities industry financial markets association | 33 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=60013 | CFTC-2011-0049 | 1 | CFTC | securities industry financial markets association | kenneth bentsen | securities industry financial markets association | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association-CIK | CIK | NA | NA | 94 | 96 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 6449 |
| info tech solutions business | 32 | https://www.regulations.gov/comment/CFPB-2016-0020-3973 | CFPB-2016-0020 | 1 | CFPB | consumer info experian information solutions | andy arculin | info tech solutions business | NA | NA | NA | NA | NA | NA | NA | info tech solutions business | 0.6806051 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | info tech solutions business-CIK | CIK | NA | NA | 1 | 1 | NA | NA | CFPB | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 419 | 3179 |
| natl assn retail collection attorneys | 32 | https://www.regulations.gov/comment/CFPB-2013-0033-0382 | CFPB-2013-0033 | 1 | CFPB | national association retail collection attorneys | joann needleman | NA | NA | NA | NA | NA | NA | NA | natl assn retail collection attorneys | natl assn retail collection attorneys | 0.9933293 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | 318333.3 | 955000 | natl assn retail collection attorneys-OpenSecrets | OpenSecrets | NA | natl assn retail collection attorneys | 5 | 5 | NA | NA | CFPB | PAC Donor (CRP Data) | All Other Rules | 318333.3 | 955000 | NA | NA | NA | NA | NA | 6837 |
| american bankers association | 32 | https://www.regulations.gov/comment/CFPB-2012-0028-2673 | CFPB-2012-0028 | 1 | CFPB | american bankers association | robert davis | NA | NA | NA | NA | NA | NA | american bankers association | NA | american bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 129958383 | 85072792 | 521001304 | NA | NA | american bankers association-Nonprofit | Nonprofit | 129958383 | NA | 100 | 101 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 129958383 | 85072792 | NA | NA | NA | 10420 |
| american bankers association | 32 | https://www.regulations.gov/comment/CFPB-2011-0006-0005 | CFPB-2011-0006 | 1 | CFPB | american bankers association | virginia oneill | NA | NA | NA | NA | NA | NA | american bankers association | NA | american bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 129958383 | 85072792 | 521001304 | NA | NA | american bankers association-Nonprofit | Nonprofit | 129958383 | NA | 100 | 101 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 129958383 | 85072792 | NA | NA | 50 | 2816 |
| american bankers association | 32 | https://www.regulations.gov/comment/CFPB-2011-0007-0005 | CFPB-2011-0007 | 1 | CFPB | american bankers association | virginia oneill | NA | NA | NA | NA | NA | NA | american bankers association | NA | american bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 129958383 | 85072792 | 521001304 | NA | NA | american bankers association-Nonprofit | Nonprofit | 129958383 | NA | 100 | 101 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 129958383 | 85072792 | NA | NA | 202 | 2816 |
| bank america | 32 | https://www.sec.gov/comments/s7-14-11/s71411-429.pdf | S7-14-11 | 1 | SEC | bank america | kenneth l miller | bank america | NA | NA | NA | NA | NA | NA | NA | bank america | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank america-CIK | CIK | NA | NA | 34 | 34 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 9582 |
| davis polk wardwell | 32 | https://www.federalreserve.gov/SECRS/2016/August/20160826/R-1538/R-1538_080516_130420_423053866808_1.pdf | R-1538 | 1 | FRS | davis polk wardwell | on behalf citigroup | NA | NA | NA | NA | NA | NA | NA | davis polk wardwell | davis polk wardwell | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | davis polk wardwell-OpenSecrets | OpenSecrets | NA | davis polk wardwell | 2 | 2 | NA | NA | FRS | PAC Donor (CRP Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 1618 | 2962 |
| davis polk wardwell | 32 | https://www.federalreserve.gov/SECRS/2017/January/20170126/R-1538/R-1538_081516_130442_365208348627_1.pdf | R-1538 | 1 | FRS | davis polk wardwell | on behalf bank america | NA | NA | NA | NA | NA | NA | NA | davis polk wardwell | davis polk wardwell | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | davis polk wardwell-OpenSecrets | OpenSecrets | NA | davis polk wardwell | 2 | 2 | NA | NA | FRS | PAC Donor (CRP Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 1718 | 2895 |
| consumer mortgage coalition | 31 | https://www.regulations.gov/comment/CFPB-2012-0028-0488 | CFPB-2012-0028 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | NA | 4406 |
| consumer mortgage coalition | 31 | https://www.regulations.gov/comment/CFPB-2012-0029-0123 | CFPB-2012-0029 | 1 | CFPB | consumer mortgage coalition | anne canfield | NA | NA | NA | NA | NA | NA | consumer mortgage coalition | NA | consumer mortgage coalition | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 325391 | 936924 | 521985066 | NA | NA | consumer mortgage coalition-Nonprofit | Nonprofit | 325391 | NA | 52 | 53 | NA | NA | CFPB | Nonprofit (IRS Data) | All Other Rules | NA | NA | 325391 | 936924 | NA | NA | 677 | 4406 |
| better markets | 31 | https://www.sec.gov/comments/s7-23-07/s72307-52.pdf | S7-23-07 | 1 | SEC | better markets | dennis m kelleher | NA | NA | NA | NA | NA | NA | better markets | NA | better markets | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 3898749 | 3022839 | 272227363 | NA | NA | better markets-Nonprofit | Nonprofit | 3898749 | NA | 156 | 158 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 3898749 | 3022839 | NA | NA | NA | 1801 |
| ryder stilwell investment advisors inc ca adv | 31 | https://www.sec.gov/comments/s7-33-10/s73310-110.pdf | S7-33-10 | 1 | SEC | americans limited government ryder systems inc financial services institute inc us chamber commerce verizon white case | NA | ryder stilwell investment advisors inc ca adv | NA | NA | NA | NA | NA | NA | NA | ryder stilwell investment advisors inc ca adv | 0.4053302 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | ryder stilwell investment advisors inc ca adv-CIK | CIK | NA | NA | 2 | 2 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 10131 | 7705 |
| ryder stilwell investment advisors inc ca adv | 31 | https://www.sec.gov/comments/s7-33-10/s73310-35.pdf | S7-33-10 | 1 | SEC | americans limited government ryder systems inc financial services institute inc us chamber commerce verizon white case | NA | ryder stilwell investment advisors inc ca adv | NA | NA | NA | NA | NA | NA | NA | ryder stilwell investment advisors inc ca adv | 0.4053302 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | ryder stilwell investment advisors inc ca adv-CIK | CIK | NA | NA | 2 | 2 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 10131 | 7705 |
| securities industry financial markets association | 31 | https://www.sec.gov/comments/s7-45-10/s74510-587.pdf | S7-45-10 | 1 | SEC | securities industry financial markets association | leslie m norwood | securities industry financial markets association | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | securities industry financial markets association-CIK | CIK | NA | NA | 94 | 96 | NA | NA | SEC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | 3083 | 7299 |
| clearing house | 31 | https://www.federalreserve.gov/SECRS/2014/August/20140813/R-1489/R-1489_070814_129556_332251404945_1.pdf | R-1489 | 1 | FRS | clearing house | american bankers association | NA | NA | NA | NA | NA | NA | NA | clearing house | clearing house | 1.0000000 | OpenSecrets | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1449500.0 | 8697000 | clearing house-OpenSecrets | OpenSecrets | NA | clearing house | 15 | 16 | NA | NA | FRS | PAC Donor (CRP Data) | All Other Rules | 1449500.0 | 8697000 | NA | NA | NA | NA | 274 | 2770 |
| bank america | 31 | https://www.federalreserve.gov/SECRS/2013/December/20131218/R-1411/R-1411_103013_111517_347817569237_1.pdf | R-1411 | 1 | FRS | bank america | kenneth l miller | bank america | NA | NA | NA | NA | NA | NA | NA | bank america | 1.0000000 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank america-CIK | CIK | NA | NA | 34 | 34 | NA | NA | FRS | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 9603 |
| erisa industry committee | 31 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=27986 | CFTC-2010-0193 | 1 | CFTC | erisa industry committee eric | mark ugoretz | NA | NA | NA | NA | NA | NA | erisa industry committee | NA | erisa industry committee | 0.8765619 | Nonprofit | NA | NA | NA | NA | NA | NA | 1206948 | 1704497 | 521077961 | NA | NA | erisa industry committee-Nonprofit | Nonprofit | 1206948 | NA | 1 | 2 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 1206948 | 1704497 | NA | NA | NA | 3135 |
| american bankers association | 30 | https://www.sec.gov/comments/s7-41-11/s74111-280.pdf | S7-41-11 | 1 | SEC | american bankers association | frank keating | NA | NA | NA | NA | NA | NA | american bankers association | NA | american bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 129958383 | 85072792 | 521001304 | NA | NA | american bankers association-Nonprofit | Nonprofit | 129958383 | NA | 100 | 101 | NA | NA | SEC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 129958383 | 85072792 | NA | NA | 1030 | 5567 |
| american bankers association | 30 | https://www.federalreserve.gov/SECRS/2012/March/20120309/R-1432/R-1432_021312_105526_519231400402_1.pdf | R-1432 | 1 | FRS | american bankers association | frank keating | NA | NA | NA | NA | NA | NA | american bankers association | NA | american bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 129958383 | 85072792 | 521001304 | NA | NA | american bankers association-Nonprofit | Nonprofit | 129958383 | NA | 100 | 101 | NA | NA | FRS | Nonprofit (IRS Data) | All Other Rules | NA | NA | 129958383 | 85072792 | NA | NA | 1006 | 5521 |
| rabobank nederland fi | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=27739 | CFTC-2012-0058 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutsche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada royal bank scotland group plc societe generale torontodominion bank ubs ag | lanny schwartz | rabobank nederland fi | NA | NA | NA | NA | NA | NA | NA | rabobank nederland fi | 0.2011722 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | rabobank nederland fi-CIK | CIK | NA | NA | 3 | 5 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| american bankers association | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=56779 | CFTC-2012-0019 | 1 | CFTC | american bankers association | frank keating | NA | NA | NA | NA | NA | NA | american bankers association | NA | american bankers association | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 129958383 | 85072792 | 521001304 | NA | NA | american bankers association-Nonprofit | Nonprofit | 129958383 | NA | 100 | 101 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 129958383 | 85072792 | NA | NA | NA | 5567 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30807 | CFTC-2010-0189 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3224204 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 6 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30804 | CFTC-2010-0179 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3224204 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 6 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30806 | CFTC-2010-0178 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3224204 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 6 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30802 | CFTC-2010-0162 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3224204 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 6 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30805 | CFTC-2010-0183 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3224204 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 6 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30801 | CFTC-2010-0166 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3432775 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 2 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30803 | CFTC-2010-0165 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3224204 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 6 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=30799 | CFTC-2010-0167 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutche bank ag hsbc nomura securities international inc rabobank nederland | lanny schwartz | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616 | 0.3432775 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | deutche bank sa institucion de banca multiple division fiduciaria trustee irrevocable trust f1616-CIK | CIK | NA | NA | 2 | 8 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| rabobank nederland fi | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=27741 | CFTC-2011-0018 | 1 | CFTC | barclays bank plc bnp paribas sa credit suisse ag deutsche bank ag hsbc nomura securities international inc rabobank nederland royal bank canada royal bank scotland group plc societe generale torontodominion bank ubs ag | lanny schwartz | rabobank nederland fi | NA | NA | NA | NA | NA | NA | NA | rabobank nederland fi | 0.2011722 | CIK | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | rabobank nederland fi-CIK | CIK | NA | NA | 3 | 5 | NA | NA | CFTC | Filed with SEC (CIK Data) | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 4819 |
| committee on capital markets regulation | 30 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=60006 | CFTC-2011-0049 | 1 | CFTC | committee on capital markets regulation | hal scott | NA | NA | NA | NA | NA | NA | committee on capital markets regulation | NA | committee on capital markets regulation | 1.0000000 | Nonprofit | NA | NA | NA | NA | NA | NA | 1631980 | 1577050 | 300406260 | NA | NA | committee on capital markets regulation-Nonprofit | Nonprofit | 1631980 | NA | 38 | 45 | NA | NA | CFTC | Nonprofit (IRS Data) | All Other Rules | NA | NA | 1631980 | 1577050 | NA | NA | NA | 1271 |
Technical terms x assets
t <- d %>% drop_na(dictionary_terms)
# FDIC ASSTS
p <- t %>%
filter(!is.na(`FDIC_Institutions-bestMatch:ASSET`),
`FDIC_Institutions-bestMatch:ASSET` > 10) %>%
ggplot() +
aes(x = `FDIC_Institutions-bestMatch:ASSET`, # %>% log(),
y = dictionary_terms ) +
geom_point(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Assets",
y = "Technical Terms",
title = "FDIC-Insured Banks")
p
p +
scale_y_log10() +
scale_x_log10()
t %>%
filter(!is.na(`FDIC_Institutions-bestMatch:ASSET`),
`FDIC_Institutions-bestMatch:ASSET` > 10,
dictionary_terms == 0) %>%
dplyr::select(org_name, everything() ) %>%
kablebox()| org_name | docket_id | comment_docket_count | comment_url | comment_agency | comment_org_name | comment_submitter_name | CIK_name | CreditUnions_name | FDIC_Institutions_name | FFIECInstitutions_name | SEC_Institutions_name | compustat_resources_name | nonprofits_resources_name | opensecrets_resources_jwVersion_name | best_match_name | best_match_score | best_match_type | FDIC_Institutions-bestMatch:ASSET | FDIC_Institutions-bestMatch:STNAME | CIK-bestMatch:marketcap | SEC_Institutions-bestMatch:Ticker | compustat_resources-bestMatch:marketcap | compustat_resources-bestMatch:naics | nonprofits_resources-bestMatch:assets | nonprofits_resources-bestMatch:revenue | nonprofits_resources-bestMatch:ein | opensecrets_resources_jwVersion-bestMatch:MeanContribAmountPerYearContributed | opensecrets_resources_jwVersion-bestMatch:TotalContribAmount | matches | org_type | org_resources | opensecrets_resources_name | org_comments | best_match_org_comments | marketcap | marketcap2 | Agency | Org_type | payday | MeanContribAmount | TotalContribAmount | assets | revenue | naics | Total Assets | efficacy | Total_Legal_Citations | dictionary_terms |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| town country bank missouri | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-1641 | CFPB | town country real estate | cindy collins | NA | NA | town country bank missouri | NA | NA | NA | NA | NA | town country bank missouri | 0.9234144 | FDIC | 26610 | Missouri | NA | NA | NA | NA | NA | NA | NA | NA | NA | town country bank missouri-FDIC | FDIC | 26610 | NA | 1 | 1 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| bank forest | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-211822 | CFPB | bank forest | allen breland | NA | NA | bank forest | NA | NA | NA | NA | NA | bank forest | 1.0000000 | FDIC | 165509 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank forest-FDIC | FDIC | 165509 | NA | 4 | 4 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| bank forest | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-211876 | CFPB | bank forest | allen breland | NA | NA | bank forest | NA | NA | NA | NA | NA | bank forest | 1.0000000 | FDIC | 165509 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank forest-FDIC | FDIC | 165509 | NA | 4 | 4 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| reliance bank | CFPB-2017-0021 | 1 | https://www.regulations.gov/comment/CFPB-2017-0021-0005 | CFPB | reliance bank | h barton buddy hann | NA | NA | reliance bank | NA | NA | NA | NA | NA | reliance bank | 1.0000000 | FDIC | 28637 | New York | NA | NA | NA | NA | NA | NA | NA | NA | NA | reliance bank-FDIC | FDIC | 28637 | NA | 2 | 2 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| citizens national bank | CFPB-2017-0021 | 1 | https://www.regulations.gov/comment/CFPB-2017-0021-0033 | CFPB | citizens national bank | della sanderford | NA | NA | citizens national bank | NA | NA | NA | NA | NA | citizens national bank | 1.0000000 | FDIC | 338179 | Connecticut | NA | NA | NA | NA | NA | NA | NA | NA | NA | citizens national bank-FDIC | FDIC | 338179 | NA | 7 | 7 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| first harrison bank | CFPB-2017-0021 | 1 | https://www.regulations.gov/comment/CFPB-2017-0021-0034 | CFPB | first harrison bank | jason pendleton | NA | NA | first harrison bank | NA | NA | NA | NA | NA | first harrison bank | 1.0000000 | FDIC | 760183 | Indiana | NA | NA | NA | NA | NA | NA | NA | NA | NA | first harrison bank-FDIC | FDIC | 760183 | NA | 5 | 5 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| university bank | CFPB-2017-0018 | 1 | https://www.regulations.gov/comment/CFPB-2017-0018-0004 | CFPB | university bank | teresa ferman | NA | NA | university bank | NA | NA | NA | NA | NA | university bank | 1.0000000 | FDIC | 65734 | Missouri | NA | NA | NA | NA | NA | NA | NA | NA | NA | university bank-FDIC | FDIC | 65734 | NA | 2 | 2 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| alden state bank | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-208809 | CFPB | alden state bank | hilde neubauer | NA | NA | alden state bank | NA | NA | NA | NA | NA | alden state bank | 1.0000000 | FDIC | 309183 | New York | NA | NA | NA | NA | NA | NA | NA | NA | NA | alden state bank-FDIC | FDIC | 309183 | NA | 4 | 4 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| colonial savings fa | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-1608 | CFPB | colonial savings bank fa | kish ivey | NA | NA | colonial savings fa | NA | NA | NA | NA | NA | colonial savings fa | 0.9987592 | FDIC | 136400 | Kansas | NA | NA | NA | NA | NA | NA | NA | NA | NA | colonial savings fa-FDIC | FDIC | 136400 | NA | 1 | 2 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| farmers merchants bank long beach | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-1609 | CFPB | farmers merchants bank long beach | angela oganezova | NA | NA | farmers merchants bank long beach | NA | NA | NA | NA | NA | farmers merchants bank long beach | 1.0000000 | FDIC | 6834068 | California | NA | NA | NA | NA | NA | NA | NA | NA | NA | farmers merchants bank long beach-FDIC | FDIC | 6834068 | NA | 1 | 1 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| first bank south | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-1624 | CFPB | first south bank | sheila greer | NA | NA | first bank south | NA | NA | NA | NA | NA | first bank south | 1.0000000 | FDIC | 156890 | Illinois | NA | NA | NA | NA | NA | NA | NA | NA | NA | first bank south-FDIC | FDIC | 156890 | NA | 1 | 1 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| columbia bank | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-1618 | CFPB | columbia bank | kathryn morris | NA | NA | columbia bank | NA | NA | NA | NA | NA | columbia bank | 1.0000000 | FDIC | 208384 | Florida | NA | NA | NA | NA | NA | NA | NA | NA | NA | columbia bank-FDIC | FDIC | 208384 | NA | 2 | 2 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| peoples intermountain bank | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-148853 | CFPB | peoples intermountain bank | jay hunsaker | NA | NA | peoples intermountain bank | NA | NA | NA | NA | NA | peoples intermountain bank | 1.0000000 | FDIC | 1682347 | Utah | NA | NA | NA | NA | NA | NA | NA | NA | NA | peoples intermountain bank-FDIC | FDIC | 1682347 | NA | 1 | 1 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| first federal arkansas fa | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-186578 | CFPB | arkansas federal credit union | karyn davis | NA | NA | first federal arkansas fa | NA | NA | NA | NA | NA | first federal arkansas fa | 0.9702488 | FDIC | 1339075 | Arkansas | NA | NA | NA | NA | NA | NA | NA | NA | NA | first federal arkansas fa-FDIC | FDIC | 1339075 | NA | 3 | 3 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| bryant bank | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-185082 | CFPB | bryant bank | david long | NA | NA | bryant bank | NA | NA | NA | NA | NA | bryant bank | 1.0000000 | FDIC | 1501632 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | bryant bank-FDIC | FDIC | 1501632 | NA | 2 | 2 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| coastal bend national bank | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-0027 | CFPB | keller williams coastal bend | char atnip | NA | NA | coastal bend national bank | NA | NA | NA | NA | NA | coastal bend national bank | 0.8568533 | FDIC | 38704 | Texas | NA | NA | NA | NA | NA | NA | NA | NA | NA | coastal bend national bank-FDIC | FDIC | 38704 | NA | 1 | 1 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| d l evans bank | CFPB-2016-0038 | 1 | https://www.regulations.gov/comment/CFPB-2016-0038-1324 | CFPB | d l evans bank | trevor matthews | NA | NA | d l evans bank | NA | NA | NA | NA | NA | d l evans bank | 1.0000000 | FDIC | 1312267 | Idaho | NA | NA | NA | NA | NA | NA | NA | NA | NA | d l evans bank-FDIC | FDIC | 1312267 | NA | 12 | 12 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| american pacific bank | CFPB-2012-0028 | 1 | https://www.regulations.gov/comment/CFPB-2012-0028-2031 | CFPB | american pacific mortgage | marty allred | NA | NA | american pacific bank | NA | NA | NA | NA | NA | american pacific bank | 0.9459827 | FDIC | 124355 | Oregon | NA | NA | NA | NA | NA | NA | NA | NA | NA | american pacific bank-FDIC | FDIC | 124355 | NA | 34 | 29 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| citizens state bank | CFPB-2013-0002 | 1 | https://www.regulations.gov/comment/CFPB-2013-0002-0073 | CFPB | citizens state bank | kathy kruger | NA | NA | citizens state bank | NA | NA | NA | NA | NA | citizens state bank | 1.0000000 | FDIC | 261907 | Oklahoma | NA | NA | NA | NA | NA | NA | NA | NA | NA | citizens state bank-FDIC | FDIC | 261907 | NA | 8 | 8 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| guardian bank | CFPB-2013-0002 | 1 | https://www.regulations.gov/comment/CFPB-2013-0002-0475 | CFPB | guardian bank | pam horton | NA | NA | guardian bank | NA | NA | NA | NA | NA | guardian bank | 1.0000000 | FDIC | 73483 | Florida | NA | NA | NA | NA | NA | NA | NA | NA | NA | guardian bank-FDIC | FDIC | 73483 | NA | 1 | 1 | NA | NA | CFPB | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | 0 | 0 |
| united community bank | S7-08-13 | 1 | https://www.sec.gov/comments/s7-08-13/s70813-39.htm | SEC | united community bank | garland certain | NA | NA | united community bank | NA | NA | NA | NA | NA | united community bank | 1.0000000 | FDIC | 34537 | Kentucky | NA | NA | NA | NA | NA | NA | NA | NA | NA | united community bank-FDIC | FDIC | 34537 | NA | 5 | 5 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| bank san diego | S7-09-15 | 1 | https://www.sec.gov/comments/s7-09-15/s70915-4.htm | SEC | san diego | michael d berlin | NA | NA | bank san diego | NA | NA | NA | NA | NA | bank san diego | 1.0000000 | FDIC | 294277 | California | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank san diego-FDIC | FDIC | 294277 | NA | 1 | 1 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| united republic bank | S7-42-10 | 1 | https://www.sec.gov/comments/s7-42-10/s74210-305.htm | SEC | united republic | semkae kilonzo | NA | NA | united republic bank | NA | NA | NA | NA | NA | united republic bank | 1.0000000 | FDIC | 108100 | Nebraska | NA | NA | NA | NA | NA | NA | NA | NA | NA | united republic bank-FDIC | FDIC | 108100 | NA | 1 | 2 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| reading cooperative bank | S7-14-11 | 1 | https://www.sec.gov/comments/s7-14-11/s71411-50.htm | SEC | reading cooperative bank | julieann m thurlow | NA | NA | reading cooperative bank | NA | NA | NA | NA | NA | reading cooperative bank | 1.0000000 | FDIC | 513042 | Massachusetts | NA | NA | NA | NA | NA | NA | NA | NA | NA | reading cooperative bank-FDIC | FDIC | 513042 | NA | 5 | 5 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| randolph savings bank | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-471.htm | SEC | randolph savings bank | liz turner | NA | NA | randolph savings bank | NA | NA | NA | NA | NA | randolph savings bank | 1.0000000 | FDIC | 482761 | Massachusetts | NA | NA | NA | NA | NA | NA | NA | NA | NA | randolph savings bank-FDIC | FDIC | 482761 | NA | 2 | 2 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| bank oldham county | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-326.htm | SEC | bank oldham county | stephen m norton | NA | NA | bank oldham county | NA | NA | NA | NA | NA | bank oldham county | 1.0000000 | FDIC | 143340 | Kentucky | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank oldham county-FDIC | FDIC | 143340 | NA | 2 | 2 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| granite savings bank | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-210.htm | SEC | granite savings bank | norman s seppala | NA | NA | granite savings bank | NA | NA | NA | NA | NA | granite savings bank | 1.0000000 | FDIC | 64975 | Massachusetts | NA | NA | NA | NA | NA | NA | NA | NA | NA | granite savings bank-FDIC | FDIC | 64975 | NA | 1 | 1 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| greenfield cooperative bank | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-209.htm | SEC | greenfield cooperative bank | anthony j worden | NA | NA | greenfield cooperative bank | NA | NA | NA | NA | NA | greenfield cooperative bank | 1.0000000 | FDIC | 578831 | Massachusetts | NA | NA | NA | NA | NA | NA | NA | NA | NA | greenfield cooperative bank-FDIC | FDIC | 578831 | NA | 4 | 4 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| greenfield cooperative bank | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-207.htm | SEC | greenfield cooperative bank | david g ahearn | NA | NA | greenfield cooperative bank | NA | NA | NA | NA | NA | greenfield cooperative bank | 1.0000000 | FDIC | 578831 | Massachusetts | NA | NA | NA | NA | NA | NA | NA | NA | NA | greenfield cooperative bank-FDIC | FDIC | 578831 | NA | 4 | 4 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| bank elk river | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-206.htm | SEC | city elk river | tim simon | NA | NA | bank elk river | NA | NA | NA | NA | NA | bank elk river | 0.9895928 | FDIC | 408374 | Minnesota | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank elk river-FDIC | FDIC | 408374 | NA | 1 | 3 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| greenfield cooperative bank | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-183.htm | SEC | greenfield cooperative bank | eric marsh | NA | NA | greenfield cooperative bank | NA | NA | NA | NA | NA | greenfield cooperative bank | 1.0000000 | FDIC | 578831 | Massachusetts | NA | NA | NA | NA | NA | NA | NA | NA | NA | greenfield cooperative bank-FDIC | FDIC | 578831 | NA | 4 | 4 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| first national bank bastrop | S7-45-10 | 1 | https://www.sec.gov/comments/s7-45-10/s74510-152.htm | SEC | first national bank bastrop | reid sharp | NA | NA | first national bank bastrop | NA | NA | NA | NA | NA | first national bank bastrop | 1.0000000 | FDIC | 532024 | Texas | NA | NA | NA | NA | NA | NA | NA | NA | NA | first national bank bastrop-FDIC | FDIC | 532024 | NA | 3 | 3 | NA | NA | SEC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| community bank | R-1443_V1 | 1 | https://www.federalreserve.gov/SECRS/2013/January/20130129/R-1443/R-1443_110512_110579_355661550171_1.pdf | FRS | community bank | david hughes | NA | NA | community bank | NA | NA | NA | NA | NA | community bank | 1.0000000 | FDIC | 569546 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | community bank-FDIC | FDIC | 569546 | NA | 15 | 15 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| community bank | R-1443_V1 | 1 | https://www.federalreserve.gov/SECRS/2013/January/20130129/R-1443/R-1443_110512_110580_355662018945_1.pdf | FRS | community bank | david j washer | NA | NA | community bank | NA | NA | NA | NA | NA | community bank | 1.0000000 | FDIC | 569546 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | community bank-FDIC | FDIC | 569546 | NA | 15 | 15 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| community bank | R-1443_V1 | 1 | https://www.federalreserve.gov/SECRS/2013/January/20130129/R-1443/R-1443_110512_110581_355662331461_1.pdf | FRS | community bank | coast | NA | NA | community bank | NA | NA | NA | NA | NA | community bank | 1.0000000 | FDIC | 569546 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | community bank-FDIC | FDIC | 569546 | NA | 15 | 15 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| compass bank | CFTC-2012-0102 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=58869 | CFTC | compass bank | brian goodrich | NA | NA | compass bank | NA | NA | NA | NA | NA | compass bank | 1.0000000 | FDIC | 83988195 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | compass bank-FDIC | FDIC | 83988195 | NA | 2 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | 65384.62 | 1700000 | NA | NA | NA | NA | NA | NA | 0 |
| regions bank | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=338 | CFTC | regions bank | ex parte communication | NA | NA | regions bank | NA | NA | NA | NA | NA | regions bank | 1.0000000 | FDIC | 123636430 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | regions bank-FDIC | FDIC | 123636430 | NA | 5 | 5 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| bank webster | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=317 | CFTC | webster bank | ex parte communication | NA | NA | bank webster | NA | NA | NA | NA | NA | bank webster | 1.0000000 | FDIC | 4242 | Georgia | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank webster-FDIC | FDIC | 4242 | NA | 4 | 4 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| first national bank in miles city | CFTC-2012-0019 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=57329 | CFTC | stockman bank montana miles city montana | bill bickle | NA | NA | first national bank in miles city | NA | NA | NA | NA | NA | first national bank in miles city | 0.6502750 | FDIC | 72868 | Montana | NA | NA | NA | NA | NA | NA | NA | NA | NA | first national bank in miles city-FDIC | FDIC | 72868 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| goldman sachs bank usa | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=884 | CFTC | goldman sachs bank usa | ex parte communication | NA | NA | goldman sachs bank usa | NA | NA | NA | NA | NA | goldman sachs bank usa | 1.0000000 | FDIC | 156156000 | New York | NA | NA | NA | NA | NA | NA | NA | NA | NA | goldman sachs bank usa-FDIC | FDIC | 156156000 | NA | 3 | 3 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| allied cypress bank | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=223 | CFTC | cypress group cypress | ex parte communication | NA | NA | allied cypress bank | NA | NA | NA | NA | NA | allied cypress bank | 0.9808917 | FDIC | 128701 | Texas | NA | NA | NA | NA | NA | NA | NA | NA | NA | allied cypress bank-FDIC | FDIC | 128701 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| peoples bank | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=27774 | CFTC | peoples bank | jack hartings | NA | NA | peoples bank | NA | NA | NA | NA | NA | peoples bank | 1.0000000 | FDIC | 11896 | Alabama | NA | NA | NA | NA | NA | NA | NA | NA | NA | peoples bank-FDIC | FDIC | 11896 | NA | 35 | 35 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| united oklahoma bank | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=238 | CFTC | bank oklahoma | ex parte communication | NA | NA | united oklahoma bank | NA | NA | NA | NA | NA | united oklahoma bank | 1.0000000 | FDIC | 171925 | Oklahoma | NA | NA | NA | NA | NA | NA | NA | NA | NA | united oklahoma bank-FDIC | FDIC | 171925 | NA | 2 | 3 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| capital one fsb | CFTC-2012-0058 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=243 | CFTC | capital one na | ex parte communication | NA | NA | capital one fsb | NA | NA | NA | NA | NA | capital one fsb | 0.9792454 | FDIC | 17487074 | Virginia | NA | NA | NA | NA | NA | NA | NA | NA | NA | capital one fsb-FDIC | FDIC | 17487074 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| privatebank trust | CFTC-2010-0196 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=417 | CFTC | privatebank trust | ex parte communication | NA | NA | privatebank trust | NA | NA | NA | NA | NA | privatebank trust | 1.0000000 | FDIC | 20401001 | Illinois | NA | NA | NA | NA | NA | NA | NA | NA | NA | privatebank trust-FDIC | FDIC | 20401001 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| vectra bank colorado national association | CFTC-2013-0107 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=1013 | CFTC | copperwood asset management lp copperwood vectra capital llc vectra | ex parte communication | NA | NA | vectra bank colorado national association | NA | NA | NA | NA | NA | vectra bank colorado national association | 0.5954048 | FDIC | 3317609 | New Mexico | NA | NA | NA | NA | NA | NA | NA | NA | NA | vectra bank colorado national association-FDIC | FDIC | 3317609 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| farmers national bank | CFTC-2013-0107 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=59661 | CFTC | national farmers organization | michael miller | NA | NA | farmers national bank | NA | NA | NA | NA | NA | farmers national bank | 0.9931716 | FDIC | 86960 | Kentucky | NA | NA | NA | NA | NA | NA | NA | NA | NA | farmers national bank-FDIC | FDIC | 86960 | NA | 1 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| great plains national bank | CFTC-2013-0107 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=59559 | CFTC | great plains national bank | terry shelby | NA | NA | great plains national bank | NA | NA | NA | NA | NA | great plains national bank | 1.0000000 | FDIC | 217138 | North Dakota | NA | NA | NA | NA | NA | NA | NA | NA | NA | great plains national bank-FDIC | FDIC | 217138 | NA | 3 | 3 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| huntington bank martinsburg national association | CFTC-2011-0049 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=1187 | CFTC | american bankers association bbt corporation bok financial comerica bank huntington national bank regions bank | ex parte communication | NA | NA | huntington bank martinsburg national association | NA | NA | NA | NA | NA | huntington bank martinsburg national association | 0.6668734 | FDIC | 136447 | West Virginia | NA | NA | NA | NA | NA | NA | NA | NA | NA | huntington bank martinsburg national association-FDIC | FDIC | 136447 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| jp morgan delaware | CFTC-2011-0049 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=1166 | CFTC | jp morgan | ex parte communication | NA | NA | jp morgan delaware | NA | NA | NA | NA | NA | jp morgan delaware | 1.0000000 | FDIC | 2812803 | Delaware | NA | NA | NA | NA | NA | NA | NA | NA | NA | jp morgan delaware-FDIC | FDIC | 2812803 | NA | 2 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| bank new york mellon trust company national association | CFTC-2011-0049 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=997 | CFTC | state street bank new york mellon northern trust | ex parte communication | NA | NA | bank new york mellon trust company national association | NA | NA | NA | NA | NA | bank new york mellon trust company national association | 0.5018417 | FDIC | 2131826 | California | NA | NA | NA | NA | NA | NA | NA | NA | NA | bank new york mellon trust company national association-FDIC | FDIC | 2131826 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| jp morgan delaware | CFTC-2011-0049 | 1 | https://comments.cftc.gov/PublicComments/ViewExParte.aspx?id=1095 | CFTC | jp morgan | ex parte communication | NA | NA | jp morgan delaware | NA | NA | NA | NA | NA | jp morgan delaware | 1.0000000 | FDIC | 2812803 | Delaware | NA | NA | NA | NA | NA | NA | NA | NA | NA | jp morgan delaware-FDIC | FDIC | 2812803 | NA | 2 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| firstmerit bank fsb | CFTC-2010-0153 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=50300 | CFTC | firstmerit bank | jason ebert | NA | NA | firstmerit bank fsb | NA | NA | NA | NA | NA | firstmerit bank fsb | 1.0000000 | FDIC | 119633 | Florida | NA | NA | NA | NA | NA | NA | NA | NA | NA | firstmerit bank fsb-FDIC | FDIC | 119633 | NA | 2 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| regional bank | CFTC-2010-0153 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=27084 | CFTC | regional bank | corey means | NA | NA | regional bank | NA | NA | NA | NA | NA | regional bank | 1.0000000 | FDIC | 251274 | Indiana | NA | NA | NA | NA | NA | NA | NA | NA | NA | regional bank-FDIC | FDIC | 251274 | NA | 5 | 5 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| regional bank | CFTC-2010-0158 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=26499 | CFTC | regional bank | corey means | NA | NA | regional bank | NA | NA | NA | NA | NA | regional bank | 1.0000000 | FDIC | 251274 | Indiana | NA | NA | NA | NA | NA | NA | NA | NA | NA | regional bank-FDIC | FDIC | 251274 | NA | 5 | 5 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| firstmerit bank fsb | CFTC-2011-0013 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=50301 | CFTC | firstmerit bank | jason ebert | NA | NA | firstmerit bank fsb | NA | NA | NA | NA | NA | firstmerit bank fsb | 1.0000000 | FDIC | 119633 | Florida | NA | NA | NA | NA | NA | NA | NA | NA | NA | firstmerit bank fsb-FDIC | FDIC | 119633 | NA | 2 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| oxford university bank | CFTC-2011-0013 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=33431 | CFTC | university oxford | simon driscoll | NA | NA | oxford university bank | NA | NA | NA | NA | NA | oxford university bank | 1.0000000 | FDIC | 131837 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | oxford university bank-FDIC | FDIC | 131837 | NA | 2 | 4 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| silicon valley bank | CFTC-2010-0115 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=4816 | CFTC | silicon valley forex | lawrence pingree | NA | NA | silicon valley bank | NA | NA | NA | NA | NA | silicon valley bank | 0.8349614 | FDIC | 45813986 | California | NA | NA | NA | NA | NA | NA | NA | NA | NA | silicon valley bank-FDIC | FDIC | 45813986 | NA | 3 | 5 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| frost bank | CFTC-2011-0013 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=28389 | CFTC | frost bank | tim mccormick | NA | NA | frost bank | NA | NA | NA | NA | NA | frost bank | 1.0000000 | FDIC | 30552661 | Texas | NA | NA | NA | NA | NA | NA | NA | NA | NA | frost bank-FDIC | FDIC | 30552661 | NA | 1 | 1 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | 2139676 | 2005846 | NA | NA | NA | NA | 0 |
| united republic bank | CFTC-2011-0013 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=28135 | CFTC | republic united states | special victim | NA | NA | united republic bank | NA | NA | NA | NA | NA | united republic bank | 0.8960139 | FDIC | 108100 | Nebraska | NA | NA | NA | NA | NA | NA | NA | NA | NA | united republic bank-FDIC | FDIC | 108100 | NA | 1 | 2 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
| regional bank | CFTC-2011-0013 | 1 | https://comments.cftc.gov/PublicComments/ViewComment.aspx?id=56717 | CFTC | regional bank | corey means | NA | NA | regional bank | NA | NA | NA | NA | NA | regional bank | 1.0000000 | FDIC | 251274 | Indiana | NA | NA | NA | NA | NA | NA | NA | NA | NA | regional bank-FDIC | FDIC | 251274 | NA | 5 | 5 | NA | NA | CFTC | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | NA | NA | 0 |
# nonprofits
p <- t %>%
filter(!is.na(assets),
assets > 10) %>%
ggplot() +
aes(x = assets,
y = dictionary_terms) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Assets",
y = "Technical Terms",
title = "Nonprofits")
p
p
# p +
# scale_y_log10() +
# scale_x_log10()
# contribution
p <- t %>%
filter(!is.na(MeanContribAmount)) %>%
ggplot() +
aes(x = MeanContribAmount/1000,
y = dictionary_terms) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Mean PAC Contribution ($1,000)",
y = "Technical Terms",
title = "Campaign Donors")
p
p +
scale_y_log10() +
scale_x_log10()
p <- t %>%
filter(!is.na(marketcap2)) %>%
ggplot() +
aes(x = marketcap2/1000000000,
y = dictionary_terms) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Market Capitalization (Billions)",
y = "Technical Terms",
title = "Publicly-Traded Companies")
p
p +
scale_y_log10() +
scale_x_log10() +
xlim(c(0, 400))
Efficacy x assets
e <- d %>% drop_na(efficacy)
# FDIC ASSTS
p <- e %>%
filter(!is.na(`FDIC_Institutions-bestMatch:ASSET`)) %>%
ggplot() +
aes(x = `FDIC_Institutions-bestMatch:ASSET`/1000, # %>% log(),
y = efficacy ) +
geom_point(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Assets ($1,000)",
y = "Words in Comment\nAdded to Final Rule",
title = "FDIC-Insured Banks")
p
p +
scale_y_log10() +
scale_x_log10()
e %>%
filter(!is.na(`FDIC_Institutions-bestMatch:ASSET`), efficacy == 0) %>%
dplyr::select(org_name, everything() ) %>%
kablebox()| org_name | docket_id | comment_docket_count | comment_url | comment_agency | comment_org_name | comment_submitter_name | CIK_name | CreditUnions_name | FDIC_Institutions_name | FFIECInstitutions_name | SEC_Institutions_name | compustat_resources_name | nonprofits_resources_name | opensecrets_resources_jwVersion_name | best_match_name | best_match_score | best_match_type | FDIC_Institutions-bestMatch:ASSET | FDIC_Institutions-bestMatch:STNAME | CIK-bestMatch:marketcap | SEC_Institutions-bestMatch:Ticker | compustat_resources-bestMatch:marketcap | compustat_resources-bestMatch:naics | nonprofits_resources-bestMatch:assets | nonprofits_resources-bestMatch:revenue | nonprofits_resources-bestMatch:ein | opensecrets_resources_jwVersion-bestMatch:MeanContribAmountPerYearContributed | opensecrets_resources_jwVersion-bestMatch:TotalContribAmount | matches | org_type | org_resources | opensecrets_resources_name | org_comments | best_match_org_comments | marketcap | marketcap2 | Agency | Org_type | payday | MeanContribAmount | TotalContribAmount | assets | revenue | naics | Total Assets | efficacy | Total_Legal_Citations | dictionary_terms |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| pine belt federal savings loan association | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-148772 | CFPB | pine federal credit union | terry tucker | NA | NA | pine belt federal savings loan association | NA | NA | NA | NA | NA | pine belt federal savings loan association | 0.9789054 | FDIC | 72626 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | pine belt federal savings loan association-FDIC | FDIC | 72626 | NA | 6 | 6 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 24 |
| pine belt federal savings loan association | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-148771 | CFPB | pine federal credit union | terry tucker | NA | NA | pine belt federal savings loan association | NA | NA | NA | NA | NA | pine belt federal savings loan association | 0.9789054 | FDIC | 72626 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | pine belt federal savings loan association-FDIC | FDIC | 72626 | NA | 6 | 6 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 116 |
| pine belt federal savings loan association | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-148775 | CFPB | pine federal credit union | terry tucker | NA | NA | pine belt federal savings loan association | NA | NA | NA | NA | NA | pine belt federal savings loan association | 0.9789054 | FDIC | 72626 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | pine belt federal savings loan association-FDIC | FDIC | 72626 | NA | 6 | 6 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 42 |
| pine belt federal savings loan association | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-148773 | CFPB | pine federal credit union | terry tucker | NA | NA | pine belt federal savings loan association | NA | NA | NA | NA | NA | pine belt federal savings loan association | 0.9789054 | FDIC | 72626 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | pine belt federal savings loan association-FDIC | FDIC | 72626 | NA | 6 | 6 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 79 |
| pine belt federal savings loan association | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-148774 | CFPB | pine federal credit union | terry tucker | NA | NA | pine belt federal savings loan association | NA | NA | NA | NA | NA | pine belt federal savings loan association | 0.9789054 | FDIC | 72626 | Mississippi | NA | NA | NA | NA | NA | NA | NA | NA | NA | pine belt federal savings loan association-FDIC | FDIC | 72626 | NA | 6 | 6 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 26 |
| first american savings loan association | CFPB-2016-0025 | 1 | https://www.regulations.gov/comment/CFPB-2016-0025-199026 | CFPB | first american loan | first american loan first american loan | NA | NA | first american savings loan association | NA | NA | NA | NA | NA | first american savings loan association | 1.0000000 | FDIC | 34249 | Illinois | NA | NA | NA | NA | NA | NA | NA | NA | NA | first american savings loan association-FDIC | FDIC | 34249 | NA | 2 | 2 | NA | NA | CFPB | FDIC-Insured Bank | Payday Loan Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 25 |
| progress bank | R-1438_V1 | 1 | https://www.federalreserve.gov/SECRS/2014/March/20140307/R-1483/R-1483_021314_112095_541706233068_1.pdf | FRS | progress bank | james d brown | NA | NA | progress bank | NA | NA | NA | NA | NA | progress bank | 1.0000000 | FDIC | 1160733 | Pennsylvania | NA | NA | NA | NA | NA | NA | NA | NA | NA | progress bank-FDIC | FDIC | 1160733 | NA | 3 | 3 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 26 |
| sound community bank | R-1438_V1 | 1 | https://www.federalreserve.gov/SECRS/2014/March/20140325/R-1483/R-1483_032514_112152_593835800716_1.pdf | FRS | sound community bank | gary l boman | NA | NA | sound community bank | NA | NA | NA | NA | NA | sound community bank | 1.0000000 | FDIC | 574740 | Washington | NA | NA | NA | NA | NA | NA | NA | NA | NA | sound community bank-FDIC | FDIC | 574740 | NA | 3 | 3 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 52 |
| progress bank | R-1482_V1 | 1 | https://www.federalreserve.gov/SECRS/2014/March/20140307/R-1482/R-1483_021314_112095_541706233068_1.pdf | FRS | progress bank | james d brown | NA | NA | progress bank | NA | NA | NA | NA | NA | progress bank | 1.0000000 | FDIC | 1160733 | Pennsylvania | NA | NA | NA | NA | NA | NA | NA | NA | NA | progress bank-FDIC | FDIC | 1160733 | NA | 3 | 3 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 26 |
| sound community bank | R-1482_V1 | 1 | https://www.federalreserve.gov/SECRS/2014/March/20140325/R-1482/R-1482_032514_112149_593395313546_1.pdf | FRS | sound community bank | gary l boman | NA | NA | sound community bank | NA | NA | NA | NA | NA | sound community bank | 1.0000000 | FDIC | 574740 | Washington | NA | NA | NA | NA | NA | NA | NA | NA | NA | sound community bank-FDIC | FDIC | 574740 | NA | 3 | 3 | NA | NA | FRS | FDIC-Insured Bank | All Other Rules | NA | NA | NA | NA | NA | NA | 0 | 0 | 50 |
# nonprofits
p <- e %>%
filter(!is.na(assets)) %>%
ggplot() +
aes(x = assets/1000,
y = efficacy) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Assets ($1,000)",
y = "Words in Comment\nAdded to Final Rule",
title = "Nonprofits")
p
p +
scale_y_log10() +
scale_x_log10()
# contribution
p <- e %>%
filter(!is.na(MeanContribAmount)) %>%
ggplot() +
aes(x = MeanContribAmount/1000,
y = efficacy) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Mean PAC Contribution ($1,000)",
y = "Words in Comment\nAdded to Final Rule",
title = "Campaign Donors")
p
p +
scale_y_log10() +
scale_x_log10()
# market cap
p <- e %>%
filter(!is.na(marketcap2)) %>%
ggplot() +
aes(x = marketcap2/1000000,
y = efficacy) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Market Capitalization ($1,000,000)",
y = "Words in Comment\nAdded to Final Rule",
title = "Publicly-traded Companies")
p
p +
scale_y_log10() +
scale_x_log10()
Efficacy x sophistication
p <- e %>%
ggplot() +
aes(x = Total_Legal_Citations,
y = efficacy) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Legal Citations",
y = "Words in Comment\nAdded to Final Rule")
p
p +
scale_y_log10() +
scale_x_log10()
p <- e %>%
#filter(!is.na(marketcap2)) %>%
ggplot() +
aes(x = dictionary_terms,
y = efficacy) +
geom_jitter(alpha = .5) +
geom_smooth(method = "lm"
) +
labs(x = "Technical Terms",
y = "Words in Comment\nAdded to Final Rule")
p
p +
scale_y_log10() +
scale_x_log10()
Regressions
# change knitr defaults
knitr::opts_chunk$set(fig.show="show",
fig.height=1,
fig.width=5,
out.width = "80%")Sophistication
NOTE: I’m using OLS for now but will switch to Poisson or Negative Binomial.
Bluebook
b %>% drop_na(assets, Total_Legal_Citations) %>%
arrange(-Total_Legal_Citations) %>%
dplyr::select(assets, Total_Legal_Citations, comment_url) %>%
kablebox()These models have the prefix mb_. The dependent variable is a count of technical terms per comment.
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Sophistication",
`2` = "Sophistication",
`3` = "Sophistication"
)
attr(rows, 'position') <- c(0)
mb_assets <- lm(Total_Legal_Citations ~ assets, data = b %>% mutate(assets = assets/10000000000))
mb_opensecrets <- glm(Total_Legal_Citations ~ MeanContribAmount,
data = b %>% mutate(MeanContribAmount = MeanContribAmount/10000))
mb_marketcap <- glm(Total_Legal_Citations ~ marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000))
models <- list(mb_assets, mb_opensecrets, mb_marketcap)
modelsummary(models)| Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
| Dependent Variable | Sophistication | Sophistication | Sophistication |
| Assets | −0.196 | ||
| (0.195) | |||
| PAC Donations | 0.000* | ||
| (0.000) | |||
| Market Capitalization | 0.274*** | ||
| (0.039) | |||
| Num.Obs. | 7987 | 2032 | 403 |
| Log.Lik. | −26515.057 | −6018.106 | −1200.858 |
| F | 1.017 | ||
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 |
modelplot(mb_opensecrets) + theme(legend.position = "none") +
labs(x = "Additional Legal Citations per Ten Thousand Dollars")
modelplot(mb_marketcap) + theme(legend.position = "none") +
labs(x = "Additional Legal Citations per Ten Billion Dollars")
Technical Terms
These models have the prefix mt_. The dependent variable is a count of technical terms per comment.
t %>% drop_na(assets, dictionary_terms) %>%
arrange(-dictionary_terms) %>%
dplyr::select(assets, dictionary_terms, comment_url) %>%
kablebox()# broken out by org type
mt_assets <- lm(dictionary_terms ~ assets,
data = t %>% mutate(assets = assets/10000000000))
mt_opensecrets <- glm(dictionary_terms ~ MeanContribAmount,
data = t %>% mutate(MeanContribAmount = MeanContribAmount/10000))
mt_marketcap <- glm(dictionary_terms ~ marketcap2,
data = t %>% mutate(marketcap2 = marketcap2/10000000000))
models <- list(mt_assets, mt_marketcap)
# FIXME
# modelsummary(models)
modelplot( mt_opensecrets) + theme(legend.position = "none") +
labs(x = "Additional Technical Terms per Ten Thousand Dollars")
modelplot(mt_marketcap) + theme(legend.position = "none") +
labs(x = "Additional Technical Terms per Ten Billion Dollars")
Efficacy
Efficacy by Assets
These models have the prefix me_. The dependent variable is the efficacy score.
# broken out by org type
mea_assets <- lm(efficacy ~ assets,
data = e %>% mutate(assets = assets/1000000))
mea_opensecrets <- glm(efficacy ~ MeanContribAmount,
data = e %>% mutate(MeanContribAmount = MeanContribAmount/1000))
mea_marketcap <- glm(efficacy ~ marketcap2,
data = e %>% mutate(marketcap2 = marketcap2/1000000))
models <- list(mea_assets, mea_opensecrets, mea_marketcap)
# FIXME
#modelsummary(models)
modelplot( mea_assets) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule per Million Dollars")
modelplot( mea_opensecrets) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule per Thousand Dollars")
modelplot(mea_marketcap) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule per Million Dollars")
Efficacy by Sophistication
These models have the prefix mes_. The dependent variable is the efficacy score.
mes_bluebook <- lm(efficacy ~ Total_Legal_Citations,
data = d )
mes_terms <- glm(efficacy ~ dictionary_terms,
data = d)
mes_terms_bluebook <- glm(efficacy ~ dictionary_terms + Total_Legal_Citations,
data = d )
models <- list(mes_terms , mes_bluebook , mes_terms_bluebook )
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Efficacy",
`2` = "Efficacy",
`3` = "Efficacy"
)
attr(rows, 'position') <- c(0)
# FIXME
# modelsummary(models)#, gof_map = gm)
modelplot(mes_terms) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule per Technical Term")
modelplot( mes_bluebook ) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule per Legal Citation")
modelplot(mes_terms_bluebook ) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule")
modelplot(models) + theme(legend.position = "none") +
labs(x = "Words Added to Final Rule")
Efficacy by Assets Mediated by Sophistication
To assess sophistication as a mediator between wealth and the influence of public comments on rules (efficacy), we estimate the average conditional marginal effect (ACME, conditional on the number of technical terms or legal citations) and average direct effect (ADE) of wealth using mediation analysis.
These models have the prefix mem_. The dependent variable is the efficacy score. The mediator is technical terms.
Assets x legal citations
library(mediation)
b$org_type %>% unique## [1] "Credit Union" "OpenSecrets" "CIK" "FDIC" "Nonprofit"# model predicting mediator, sophistication
model.m <- lm(Total_Legal_Citations ~ assets * org_type,
data = b %>% mutate(assets = assets/10000000000) %>%
drop_na(Total_Legal_Citations, efficacy))
# model predicting DV
model.y <- glm(efficacy ~ Total_Legal_Citations + assets * org_type,
data = b %>% mutate(assets = assets/10000000000))
models <- list(model.m, model.y)
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Legal Citations",
`2` = "Efficacy",
)
attr(rows, 'position') <- c(0)
modelsummary(models)| Model 1 | Model 2 | |
|---|---|---|
| Dependent Variable | Legal Citations | Efficacy |
| Assets | −0.797 | −100.786 |
| (4.022) | (97.728) | |
| org_typeCredit Union | −0.886 | −255.386*** |
| (2.147) | (52.164) | |
| org_typeNonprofit | 1.113 | −199.874*** |
| (1.551) | (37.695) | |
| assets:org_typeCredit Union | 0.626 | 101.121 |
| (4.081) | (99.159) | |
| assets:org_typeNonprofit | −11.227 | 82.545 |
| (9.650) | (234.555) | |
| Legal Citations | 11.848*** | |
| (0.612) | ||
| Num.Obs. | 1584 | 1584 |
| Log.Lik. | −6047.062 | −11100.023 |
| F | 0.869 | |
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 |
med.cont <- mediate(model.m, model.y, sims=1000, treat = "assets",
mediator = "Total_Legal_Citations")
summary(med.cont)##
## Causal Mediation Analysis
##
## Quasi-Bayesian Confidence Intervals
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME -128.899 -313.144 52.42 0.17
## ADE -4.704 -383.456 385.78 0.98
## Total Effect -133.602 -569.289 287.19 0.55
## Prop. Mediated 0.461 -5.534 6.23 0.51
##
## Sample Size Used: 1584
##
##
## Simulations: 1000plot(med.cont, main = "Legal Citations as a Mediator Between\nAssets and Lobbying Success",
xlab = "Words From Comment Added to Final Rule")
#modelplot(med.cont) + labs()Assets x technical terms
# model predicting mediator, sophistication
model.m <- lm(dictionary_terms ~ assets,
data = b %>% mutate(assets = assets/10000000000) %>%
drop_na(dictionary_terms, efficacy))
# model predicting DV
model.y <- glm(efficacy ~ dictionary_terms + assets,
data = b %>% mutate(assets = assets/10000000000))
models <- list(model.m, model.y)
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Technical Terms",
`2` = "Efficacy",
)
attr(rows, 'position') <- c(0)
modelsummary(models)| Model 1 | Model 2 | |
|---|---|---|
| Dependent Variable | Technical Terms | Efficacy |
| Assets | −100.512 | −5.367 |
| (128.520) | (12.890) | |
| Technical Terms | 0.093*** | |
| (0.003) | ||
| Num.Obs. | 1584 | 1584 |
| Log.Lik. | −14430.456 | −10787.024 |
| F | 0.612 | |
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 |
med.cont <- mediate(model.m, model.y, sims=1000, treat = "assets",
mediator = "dictionary_terms")
summary(med.cont)##
## Causal Mediation Analysis
##
## Quasi-Bayesian Confidence Intervals
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME -9.441 -32.495 14.61 0.44
## ADE -4.875 -30.621 22.05 0.72
## Total Effect -14.316 -48.685 22.23 0.42
## Prop. Mediated 0.536 -5.432 5.51 0.38
##
## Sample Size Used: 1584
##
##
## Simulations: 1000plot(med.cont,
main = "Technical Terms as a Mediator Between\nAssets and Lobbying Success",
xlab = "Words from Comment Added to Final Rule")
Market cap x legal citations
# model predicting mediator, sophistication
model.m <- lm(Total_Legal_Citations ~ marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000) %>%
drop_na(Total_Legal_Citations, efficacy))
# model predicting DV
model.y <- glm(efficacy ~ Total_Legal_Citations + marketcap2,
data = b %>% mutate(assets = marketcap2/10000000000))
models <- list(model.m, model.y)
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Legal Citations",
`2` = "Efficacy",
)
attr(rows, 'position') <- c(0)
modelsummary(models)| Model 1 | Model 2 | |
|---|---|---|
| Dependent Variable | Legal Citations | Efficacy |
| Market Capitalization | 0.144* | 0.000 |
| (0.072) | (0.000) | |
| Legal Citations | 32.407*** | |
| (3.667) | ||
| Num.Obs. | 133 | 133 |
| Log.Lik. | −429.850 | −926.353 |
| F | 3.960 | |
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 |
med.cont <- mediate(model.m, model.y, sims=1000, treat = "marketcap2",
mediator = "Total_Legal_Citations")
summary(med.cont)##
## Causal Mediation Analysis
##
## Quasi-Bayesian Confidence Intervals
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 4.679253662786 0.093066308580 9.63 0.044
## ADE 0.000000000267 -0.000000000362 0.00 0.398
## Total Effect 4.679253663053 0.093066308671 9.63 0.044
## Prop. Mediated 0.999999999946 0.999999999548 1.00 <0.0000000000000002
##
## ACME *
## ADE
## Total Effect *
## Prop. Mediated ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 133
##
##
## Simulations: 1000plot(med.cont,
main = "Legal Citations as a Mediator Between\nAssets and Lobbying Success",
xlab = "Words from Comment Added to Final Rule")
Market cap x technical terms
# model predicting mediator, sophistication
model.m <- lm(dictionary_terms ~ marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000) %>%
drop_na(dictionary_terms, efficacy))
# model predicting DV
model.y <- glm(efficacy ~ dictionary_terms + marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000))
models <- list(model.m, model.y)
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Technical Terms",
`2` = "Efficacy",
)
attr(rows, 'position') <- c(0)
modelsummary(models)| Model 1 | Model 2 | |
|---|---|---|
| Dependent Variable | Technical Terms | Efficacy |
| Market Capitalization | 52.010* | 1.230 |
| (25.277) | (2.531) | |
| Technical Terms | 0.115*** | |
| (0.009) | ||
| Num.Obs. | 133 | 133 |
| Log.Lik. | −1208.764 | −900.063 |
| F | 4.234 | |
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 |
med.cont <- mediate(model.m, model.y, sims=1000, treat = "marketcap2",
mediator = "dictionary_terms")
summary(med.cont)##
## Causal Mediation Analysis
##
## Quasi-Bayesian Confidence Intervals
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 6.08959 0.24382 11.85 0.042 *
## ADE 1.25301 -3.41426 6.31 0.622
## Total Effect 7.34260 0.15649 14.79 0.046 *
## Prop. Mediated 0.82441 -0.00668 2.51 0.056 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 133
##
##
## Simulations: 1000plot(med.cont,
main = "Techical Terms as a Mediator Between\nAssets and Lobbying Success",
xlab = "Words from Comment Added to Final Rule")
Market cap x technical terms x legal citations
# model predicting mediator, sophistication
model.m1 <- lm(dictionary_terms ~ marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000) %>%
drop_na(dictionary_terms, efficacy))
model.m2 <- lm(Total_Legal_Citations ~ marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000) %>%
drop_na(Total_Legal_Citations, efficacy))
# model predicting DV
model.y <- glm(efficacy ~ dictionary_terms + Total_Legal_Citations + marketcap2,
data = b %>% mutate(marketcap2 = marketcap2/10000000000))
models <- list(model.m1, model.m2, model.y)
rows <- tibble(
term = c("Dependent Variable"),
`1` = "Technical Terms",
`2` = "Legal Citations",
`3` = "Efficacy",
)
attr(rows, 'position') <- c(0)
modelsummary(models)| Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
| Dependent Variable | Technical Terms | Legal Citations | Efficacy |
| Market Capitalization | 52.010* | 0.144* | 0.827 |
| (25.277) | (0.072) | (2.495) | |
| Technical Terms | 0.097*** | ||
| (0.012) | |||
| Legal Citations | 9.406* | ||
| (4.031) | |||
| Num.Obs. | 133 | 133 | 133 |
| Log.Lik. | −1208.764 | −429.850 | −897.313 |
| F | 4.234 | 3.960 | |
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 |
med.cont <- mediate(model.m1, model.y, sims=1000, treat = "marketcap2",
mediator = "dictionary_terms")
summary(med.cont)##
## Causal Mediation Analysis
##
## Quasi-Bayesian Confidence Intervals
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 5.083 0.318 10.29 0.038 *
## ADE 0.831 -3.699 5.51 0.734
## Total Effect 5.914 -1.129 13.13 0.098 .
## Prop. Mediated 0.832 -1.248 3.57 0.096 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 133
##
##
## Simulations: 1000plot(med.cont, main = "Technical Terms as a Mediator Between\nAssets and Lobbying Success",
xlab = "Words from Comment Added to Final Rule")
med.cont <- mediate(model.m2, model.y, sims=1000, treat = "marketcap2",
mediator = "Total_Legal_Citations")
summary(med.cont)##
## Causal Mediation Analysis
##
## Quasi-Bayesian Confidence Intervals
##
## Estimate 95% CI Lower 95% CI Upper p-value
## ACME 1.3423 -0.0532 3.56 0.066 .
## ADE 0.8981 -4.2177 5.78 0.720
## Total Effect 2.2404 -2.9013 7.58 0.394
## Prop. Mediated 0.3490 -4.7305 3.98 0.408
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Sample Size Used: 133
##
##
## Simulations: 1000plot(med.cont, main = "Legal Citations as a Mediator Between\nAssets and Lobbying Success",
xlab = "Words from Comment Added to Final Rule")
#FI
# modelsummary::modelsummary(med.cont)Save data
n_comments <- nrow(efficacyXsophistication)
save(n_comments,
efficacyXsophistication,
file = here::here("data", "efficacyXsophistication.Rdata"))TODO
Presentation
Predicted probability plots for all models presented in the paper. These should replace all tables. All tables should appear in the appendix.
Nonprofit and credit union plots for the correlation between assets and sophsitication
assets-tech-figures should have x-axis scales in the millions or billions
Analysis
- split out FDIC banks and nonprofits in asset mediation analysis? (at the moment, neither type of asset is correlated with efficacy, so mediation analysis is a low priority)
Data
check on the status of OCC comments (missing from the attachments table as of May 2022)
Try to get efficacy measures for key observations. For example, in cases where we have market cap:
Observations for which we have market cap and sophistication but are missing efficacy measures (POSSIBLY DUE TO THERE BEING NO FINAL RULE):
b %>% drop_na(marketcap, Total_Legal_Citations) %>%
arrange(-Total_Legal_Citations) %>%
filter(is.na(efficacy)) %>%
dplyr::select(efficacy,marketcap, Total_Legal_Citations, org_name, comment_url) %>%
kablebox()